/;jiddlZddlZddlmZmZmZmZddlZddl Z ddl Z ddl m cmZddl mZmZmZddlmZmZddlmZmZmZee jjeje jee jjeejee jfZeZdZdZGd d eZ Gd d e Z!Gd de Z"Gdde Z#dS)N)ListOptionalTupleUnion)Image ImageFilterImageOps) ConfigMixinregister_to_config) CONFIG_NAMEPIL_INTERPOLATION deprecatect|tjjp.t|tjt jfo|jdvS)N)) isinstancePILrnpndarraytorchTensorndimimages S/root/voice-cloning/.venv/lib/python3.11/site-packages/diffusers/image_processor.pyis_valid_imager)s? eSY_ - - wEBJPUP\C]1^1^1wchcmqwcwwct|tjtjfr |jdkrdSt |rdSt|trtd|DSdS)NTc34K|]}t|VdSN)r.0rs r z+is_valid_image_imagelist..8s*==U>%((======rF) rrrrrrrlistallimagess ris_valid_image_imagelistr*-sy &2:u|455>&+:J:Jt   >t FD ! !>==f====== 5rceZdZdZeZe d4deded ed e d ed ed edeffd Z e de j deejjfdZe deeejjejjfde j fdZe de j dejfdZe dejde j fdZe dee j ejfdee j ejffdZe dee j ejfdee j ejffdZe dejjdejjfdZe dejjdejjfdZe d5dejjdedejjfdZe d6dejjded efd!Zdejjded edejjfd"Zdejjded edejjfd#Z d7deejje j ejfd eded%e deejje j ejff d&Z dejjdejjfd'Z! d8deejje j ejfd e"ede"ede#eeffd)Z$ d9de%d e"ede"ed%e d*e"e#eeeefdejf d+Z& d:dejd-e d.e"eedeejje j ejffd/Z' d;d0ejjd1ejjdejjd2e"e#eeeefdejjf d3Z(xZ)S)<VaeImageProcessorai Image processor for VAE. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. Can accept `height` and `width` arguments from [`image_processor.VaeImageProcessor.preprocess`] method. vae_scale_factor (`int`, *optional*, defaults to `8`): VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor. resample (`str`, *optional*, defaults to `lanczos`): Resampling filter to use when resizing the image. do_normalize (`bool`, *optional*, defaults to `True`): Whether to normalize the image to [-1,1]. do_binarize (`bool`, *optional*, defaults to `False`): Whether to binarize the image to 0/1. do_convert_rgb (`bool`, *optional*, defaults to be `False`): Whether to convert the images to RGB format. do_convert_grayscale (`bool`, *optional*, defaults to be `False`): Whether to convert the images to grayscale format. Tr lanczosF do_resizevae_scale_factorvae_latent_channelsresample do_normalize do_binarizedo_convert_rgbdo_convert_grayscalec tt|r|rtdddSdS)Nz`do_convert_rgb` and `do_convert_grayscale` can not both be set to `True`, if you intended to convert the image into RGB format, please set `do_convert_grayscale = False`.z` if you intended to convert the image into grayscale format, please set `do_convert_rgb = False`)super__init__ ValueError) selfr/r0r1r2r3r4r5r6 __class__s rr9zVaeImageProcessor.__init__TsZ   2 tr     rr)returnc|jdkr|d}|dzd}|jddkr d|D}n d|D}|S) zL Convert a numpy image or a batch of images to a PIL image. rN.uint8r c^g|]*}tj|d+SLmoder fromarraysqueezer#s r z2VaeImageProcessor.numpy_to_pil..r/YYY%/%--//DDDYYYrc6g|]}tj|SrrIr#s rrKz2VaeImageProcessor.numpy_to_pil..ts"EEEU%/%00EEErrroundastypeshaper) pil_imagess r numpy_to_pilzVaeImageProcessor.numpy_to_pilhs ;!  I&F3,%%''..w77 < q YYRXYYYJJEEfEEEJrczt|ts|g}d|D}tj|d}|S)N Convert a PIL image or a list of PIL images to NumPy arrays. cvg|]6}tj|tjdz 7S)go@rarrayrRfloat32r#s rrKz2VaeImageProcessor.pil_to_numpy..s5QQQ"(5//((44u<QQQrraxisrr&rstackr(s r pil_to_numpyzVaeImageProcessor.pil_to_numpyxsI &$'' XFQQ&QQQ&q))) rc|jdkr|d}tj|dddd}|S)z< Convert a NumPy image to a PyTorch tensor. r).Nrr r)rr from_numpy transposer(s r numpy_to_ptzVaeImageProcessor.numpy_to_ptsD ;!  I&F!&"2"21aA">">?? rc|dddd}|S)z< Convert a PyTorch tensor to a NumPy image. rrrr )cpupermutefloatnumpyr(s r pt_to_numpyzVaeImageProcessor.pt_to_numpysB %%aAq117799??AA rcd|zdz S)z5 Normalize an image array to [-1,1]. g@g?rNr(s r normalizezVaeImageProcessor.normalizes V|c!!rc:|dz dzddS)z6 Denormalize an image array to [0,1]. r?rr )clampr(s r denormalizezVaeImageProcessor.denormalizes#  S ''1---rrc0|d}|S)z5 Converts a PIL image to RGB format. RGBconvertrs rconvert_to_rgbz VaeImageProcessor.convert_to_rgbs  e$$ rc0|d}|S)z; Converts a PIL image to grayscale format. rErtrs rconvert_to_grayscalez&VaeImageProcessor.convert_to_grayscales  c"" r blur_factorcT|tj|}|S)z4 Applies Gaussian blur to an image. )filterr GaussianBlur)rrys rblurzVaeImageProcessor.blurs%  [5kBBCC rr mask_imagewidthheightc |d}tj|}|j\}}d}t |D]+}|dd|fdksn|dz },d} t t |D]+}|dd|fdksn| dz } ,d} t |D]'}||dksn| dz } (d} t t |D]'}||dksn| dz } (tt||z dtt| |z dtt|| z |z|tt|| z |z|f\} } }}|| z || z z }||z }||krr|| z |z }t||| z z }| |dzz} |||dzz z }||j kr||j z }||z}| |z} | dkr || z}| | z} ||j kr|j }nq|| z |z}t||| z z }| |dzz} |||dzz z }||j kr||j z }||z}| |z} | dkr || z}| | z} ||j kr|j }| | ||fS)a Finds a rectangular region that contains all masked ares in an image, and expands region to match the aspect ratio of the original image; for example, if user drew mask in a 128x32 region, and the dimensions for processing are 512x512, the region will be expanded to 128x128. Args: mask_image (PIL.Image.Image): Mask image. width (int): Width of the image to be processed. height (int): Height of the image to be processed. pad (int, optional): Padding to be added to the crop region. Defaults to 0. Returns: tuple: (x1, y1, x2, y2) represent a rectangular region that contains all masked ares in an image and matches the original aspect ratio. rErNr r) rurr[rSranger'reversedintmaxminrr)r~rrpadmaskhw crop_lefti crop_rightcrop_top crop_bottomx1y1x2y2ratio_crop_regionratio_processingdesired_heightdesired_height_diffdiff desired_widthdesired_width_diffs rget_crop_regionz!VaeImageProcessor.get_crop_regionsy$ '',, x ##z1 q  AAJ!O((**  NII %((##  AAJ!O((**  !OJJq  AGqL%%''  MHH %((##  AGqL%%''  1 KK IOQ'' ( ( HsNA&& ' ' A NS(!,, - - A Oc)1-- . .  BB "Wb1 6> / / / 2g)99N"%nR&@"A"A  %* *B %(;q(@@ @BZ&&&J--d d AvvbbZ&&&&"W(88M!$]b2g%>!?!?  $) )B $'9Q'>> >BZ%%%J,,d d AvvbbZ%%%%2r2~rc ||z }|j|jz }||kr|n|j|z|jz}||kr|n|j|z|jz}|||ftd}t jd||f} | ||dz|dzz |dz|dzz f||kr|dz|dzz } | dkrs| ||| fdd|dfd| ||| fd|j||jfd| |zfn||kr|dz|dzz } | dkrs| || |fddd|fd| || |f|jd|j|f| |zdf| S)an Resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image. Args: image: The image to resize. width: The width to resize the image to. height: The height to resize the image to. r.r2rsrboxr)rrrrresizerrnewpaste) r;rrrratio src_ratiosrc_wsrc_hresizedres fill_height fill_widths r_resize_and_fillz"VaeImageProcessor._resize_and_fills( K%,. ** f0D 0T9,,%,2F%+2U,,u~8I)8T,UUiv// ' UaZ 71uPQz9QR SSS 9   A+ 2KQ '..%)=Aq%QRCS.TTZ` aaa NNE;#7aQVX_Xf=gNhhK%/0Y  !eqj0JA~~ '..*f)=Aq!VCT.UU[a bbb NNJ#7gmQPWP]_e=fNgg#e+Q/  rcb||z }|j|jz }||kr|n|j|z|jz}||kr|n|j|z|jz}|||ftd}t jd||f} | ||dz|dzz |dz|dzz f| S)a_ Resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess. Args: image: The image to resize. width: The width to resize the image to. height: The height to resize the image to. r.rrsrrr) r;rrrrrrrrrs r_resize_and_cropz"VaeImageProcessor._resize_and_cropGsK%,. ** f0D 0T9,,%,2F%+2U,,u~8I)8T,UUiv// ' UaZ 71uPQz9QR SSS rdefault resize_modec|dkr1t|tjjstd|t|tjjr|dkr/|||ft |jj}n|dkr||||}n|dkr| |||}ntd|dt|tj r)tj j |||f}nlt|tjrR||}tj j |||f}||}|S) a Resize image. Args: image (`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`): The image input, can be a PIL image, numpy array or pytorch tensor. height (`int`): The height to resize to. width (`int`): The width to resize to. resize_mode (`str`, *optional*, defaults to `default`): The resize mode to use, can be one of `default` or `fill`. If `default`, will resize the image to fit within the specified width and height, and it may not maintaining the original aspect ratio. If `fill`, will resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image. If `crop`, will resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess. Note that resize_mode `fill` and `crop` are only supported for PIL image input. Returns: `PIL.Image.Image`, `np.ndarray` or `torch.Tensor`: The resized image. rz2Only PIL image input is supported for resize_mode rfillcropz resize_mode  is not supported)size)rrrr:rrconfigr2rrrrnn functional interpolaterrrerk)r;rrrrs rrzVaeImageProcessor.resizeas< ) # #Jucio,N,N #_R]__`` ` eSY_ - - ,i'' eV_?PQUQ\Qe?f gg&&--eUFCC&&--eUFCC !N !N!N!NOOO u| , , ,H'33e_4EErz * * ,$$U++EH'33e_4E$$U++E rc*d||dk<d||dk<|S)a- Create a mask. Args: image (`PIL.Image.Image`): The image input, should be a PIL image. Returns: `PIL.Image.Image`: The binarized image. Values less than 0.5 are set to 0, values greater than 0.5 are set to 1. rror rN)r;rs rbinarizezVaeImageProcessor.binarizes%eckesl rNc|\t|tjjr|j}n5t|tjr|jd}n |jd}|\t|tjjr|j}n5t|tjr|jd}n |jd}fd||fD\}}||fS)aF This function return the height and width that are downscaled to the next integer multiple of `vae_scale_factor`. Args: image(`PIL.Image.Image`, `np.ndarray` or `torch.Tensor`): The image input, can be a PIL image, numpy array or pytorch tensor. if it is a numpy array, should have shape `[batch, height, width]` or `[batch, height, width, channel]` if it is a pytorch tensor, should have shape `[batch, channel, height, width]`. height (`int`, *optional*, defaults to `None`): The height in preprocessed image. If `None`, will use the height of `image` input. width (`int`, *optional*`, defaults to `None`): The width in preprocessed. If `None`, will use the width of the `image` input. Nrr rc3<K|]}||jjzz VdSr")rr0)r$xr;s rr%z=VaeImageProcessor.get_default_height_width..sC  56ADK00 0      r)rrrrrrrSr)r;rrrs` rget_default_height_widthz*VaeImageProcessor.get_default_height_widths* >%11 (E5<00 (QQ =%11 ' E5<00 ' A A    ;@&/   vu}r crops_coordsc@ tjjtjtjf}jjrt|tjtjfry|j dkrnt|tjr| d}n>|j ddkrtj |d}ntj |d}t|trat|dtjrA|dj dkr0tjdt tj|d}t|trat|dtjrA|dj dkr0tjdt t j|d}t'|s/t)d d d |Dt|ts|g}t|dtjjrfd |D}jjr1|d\fd|D}jjrfd|D}njjrfd|D}|}|}nt|dtjr|dj dkrtj|dntj|d}|}|\jjr|}nt|dtjr|dj dkrt j|dnt j|d}jjr |j dkr| d}|j d}|dkr|S|\jjr|}jj}|r_|dkrGtjd|d|dt d}|r |}jj!r"|}|S)at Preprocess the image input. Args: image (`pipeline_image_input`): The image input, accepted formats are PIL images, NumPy arrays, PyTorch tensors; Also accept list of supported formats. height (`int`, *optional*, defaults to `None`): The height in preprocessed image. If `None`, will use the `get_default_height_width()` to get default height. width (`int`, *optional*`, defaults to `None`): The width in preprocessed. If `None`, will use get_default_height_width()` to get the default width. resize_mode (`str`, *optional*, defaults to `default`): The resize mode, can be one of `default` or `fill`. If `default`, will resize the image to fit within the specified width and height, and it may not maintaining the original aspect ratio. If `fill`, will resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image. If `crop`, will resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess. Note that resize_mode `fill` and `crop` are only supported for PIL image input. crops_coords (`List[Tuple[int, int, int, int]]`, *optional*, defaults to `None`): The crop coordinates for each image in the batch. If `None`, will not crop the image. rr rBrr]r zPassing `image` as a list of 4d np.ndarray is deprecated.Please concatenate the list along the batch dimension and pass it as a single 4d np.ndarrayzPassing `image` as a list of 4d torch.Tensor is deprecated.Please concatenate the list along the batch dimension and pass it as a single 4d torch.Tensorz9Input is in incorrect format. Currently, we only support , c34K|]}t|VdSr")str)r$rs rr%z/VaeImageProcessor.preprocess..s-UxUxabVYZ[V\V\UxUxUxUxUxUxrNc:g|]}|SrN)r)r$rrs rrKz0VaeImageProcessor.preprocess.. s%===! --===rcBg|]}|S))rr)r$rrrr;rs rrKz0VaeImageProcessor.preprocess..#s.___TUQ;OO___rc:g|]}|SrN)rvr$rr;s rrKz0VaeImageProcessor.preprocess..%s'???A,,Q//???rc:g|]}|SrN)rxrs rrKz0VaeImageProcessor.preprocess..'s'EEE!22155EEErPassing `image` as torch tensor with value range in [-1,1] is deprecated. The expected value range for image tensor is [0,1] when passing as pytorch tensor or numpy Array. You passed `image` with value range [,]F)#rrrrrrrr6rr unsqueezerS expand_dimsr&warningswarn FutureWarning concatenatecatr*r:joinr/rr5rarer`rr3rrrmr4r) r;rrrrrsupported_formatschannelr3s ` ```` r preprocesszVaeImageProcessor.preprocesss;>!Y_bj%,G ; + ; 55.~> j j jq>!+< JT  eAh ' ' '%( j j jrrr) rrrr:typerrr3rSr`rrkrV)r;rrrdeprecation_messages`` ` r postprocesszVaeImageProcessor.postprocessUsV,%.. qDKKqqq  ; ; ;.;...  /:M]b c c c cK ( " "L  !"k67%+a.HN j j j j j jTYZ_ZefgZhTiTi j j j   $  L  '' $  L %  $$U++ + rr init_image crop_coordsc(|j|j}}||||}||||}tjd||f}||ddtj |d|d}|y|\}} } } | |z } | | z } tjd||f}||| | d}|||| f|d }|d}| ||d }|S) zB overlay the inpaint output to the original image )rrRGBaRGBArE)rNr)rrrrs) rrrrrrrrur invertalpha_composite)r;rrrrrrinit_image_maskedryrrrr base_images r apply_overlayzVaeImageProcessor.apply_overlays~ U\v[[5[HH {{4uV{<<IMM&5&/BB 2 26 : : B B6 J JQYQ`aeamamnqararQsQsttt-55f==  "&LAq"bQAQAvv??JKKaqfKMME   UQF + + +&&u--E f%% /000 e$$ r)Tr-r r.TFFF)r )r)r)NN)NNrNrNr")*__name__ __module__ __qualname____doc__r config_namer boolrrr9 staticmethodrrrrrrVrrarrrerkrmrqrvrxr}rrrrrrrrPipelineImageInputrrr __classcell__r<s@rr,r,<s,*K !#$!!!$%*!     #& RZ D,A   \  U4 #8#)/#IJ rz   \ BJ5<\ELRZ\"% EL 89"eBJPUP\D\>]"""\" .E"*el":;.bjRWR^F^@_...\. cio#)/\CIO \CIO#cio\WWCIOWCWWWW\Wr+y++ +  ++++Zy   >% 66SY_bj%,>?66 6  6 sy EL8 9 6666pcio#)/(!%# ))SY_bj%,>?) )} ) sCx ))))\!%#$<@ ~~!~ ~} ~  ~ uS#sC%789 ~ ~~~~F!/3 5,5,|5,5,!d, 5, sy EL8 9 5,5,5,5,x<@ !!io!IO!y ! eCc3$678 !  !!!!!!!!rr,c eZdZdZeZe ddedede deffd Z e d e j d eejjfd Ze d eeejjejjfd e j fd Ze dee j ejfd ee j ejffdZd e j d eejjfdZ ddejde deeed eejje j ejffdZ ddeejejje j fdeejejje j fdeedeedeed ejf dZxZS)VaeImageProcessorLDM3Da Image processor for VAE LDM3D. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. vae_scale_factor (`int`, *optional*, defaults to `8`): VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor. resample (`str`, *optional*, defaults to `lanczos`): Resampling filter to use when resizing the image. do_normalize (`bool`, *optional*, defaults to `True`): Whether to normalize the image to [-1,1]. Tr-r.r/r0r2r3cHtdSr"r8r9)r;r/r0r2r3r<s rr9zVaeImageProcessorLDM3D.__init__s! rr)r=c|jdkr|d}|dzd}|jddkr d|D}n d|D}|S) zL Convert a NumPy image or a batch of images to a PIL image. rr?r@rArBr c^g|]*}tj|d+SrDrHr#s rrKz7VaeImageProcessorLDM3D.numpy_to_pil..rLrc Tg|]%}tj|ddddddf&SNrrOr#s rrKz7VaeImageProcessorLDM3D.numpy_to_pil..s8OOOu%/%111bqb/::OOOrrPrTs rrVz#VaeImageProcessorLDM3D.numpy_to_pils ;!  I&F3,%%''..w77 < q YYRXYYYJJOOOOOJrczt|ts|g}d|D}tj|d}|S)rXcvg|]6}tj|tjdz 7S)irZr#s rrKz=VaeImageProcessorLDM3D.depth_pil_to_numpy..s5WWWu"(5//((44 BWWWrrr]r_r(s rdepth_pil_to_numpyz)VaeImageProcessorLDM3D.depth_pil_to_numpysJ &$'' XFWWPVWWW&q))) rrcF|dddddfdz|dddddfzS)z\ Args: image: RGB-like depth image Returns: depth map Nr rrNrs rrgblike_to_depthmapz*VaeImageProcessorLDM3D.rgblike_to_depthmaps8QQQ1W~$uQQQ1W~55rc|jdkr|d}|ddddddddf}|jddkr9|dzd}fd|D}nO|jdd kr/|d ztj}d |D}nt d |S) zR Convert a NumPy depth image or a batch of images to a PIL image. rr?NrBr@rAcbg|]+}tj|d,SzI;16rF)rrIr)r$ image_depthr;s rrKz9VaeImageProcessorLDM3D.numpy_to_depth..sCXc 8 8 E EFSSSrr g@c:g|]}tj|dSrrO)r$rs rrKz9VaeImageProcessorLDM3D.numpy_to_depth..s'ddd %/+FCCCdddrz Not supported)rrSrQrRruint16 Exception)r;r) images_depthrUs` rnumpy_to_depthz%VaeImageProcessorLDM3D.numpy_to_depths ;!  I&FaaaAAAqrrk* < q (3.5577>>wGGLgsJJ\"  " "(72::29EELddWcdddJJO,, ,rrNrrcttjs tdt d|dvrd|d}t dd|d d }jjgjd ztj fd tjd D |d kr^jddkr#tj fdDd }nd d d d d d dd f}d d d d d d d df|fS|dkr* fStd|d)rrrrrrrrFrrNrcfg|]-}|r|n|.SrNrrs rrKz6VaeImageProcessorLDM3D.postprocess..,rrrBrc Xg|]&}|ddddddf'Sr )r)r$imr;s rrKz6VaeImageProcessorLDM3D.postprocess..3s>'_'_'_SU(@(@AAAqqq!""H(N(N'_'_'_rr]rrz This type r)rrrr:rrrr3rSr`rrkrrVrr)r;rrrrrs`` ` rrz"VaeImageProcessorLDM3D.postprocesss,%.. qDKKqqq  ; ; ;.;...  /:M]b c c c cK  !"k67%+a.HN j j j j j jTYZ_ZefgZhTiTi j j j    '' $  {2!## h'_'_'_'_Y^'_'_'_fghhh #AAAqqq!!!QRRK0 AAAqqq"1"%{2 2 %  $$U++T-@-@-G-GG GGGGGHH Hrrgbdepthrr target_resc8tjjtjtjfjjr@t|tjtjfr|j dkrtdt|r|g}|g}nbt|trtfd|Ds2tdd|Dddt|dtjjrÉjjrtdjjs|rD|s|dn|\fd |D}fd |D}|}|}|}|}not|dtjr|dj d krtj|d ntj|d }|}|\jjr|}|dj d krtj|d ntj|d }|}|\jjr|}n/t|dtjrtdjj}|dkrI|rGt5jd |d|dt:d}|r*|}|}jjr* |} |}||fS)zo Preprocess the image input. Accepted formats are PIL images, NumPy arrays or PyTorch tensors. rzThis is not yet supportedc38K|]}t|VdSr")r)r$rrs rr%z4VaeImageProcessorLDM3D.preprocess..Qs//^/^UV 1>O0P0P/^/^/^/^/^/^rzInput is in incorrect format: c,g|]}t|SrN)r)r$rs rrKz5VaeImageProcessorLDM3D.preprocess..Ss1G1G1Ga$q''1G1G1Grz. Currently, we only support rrc>g|]}|SrNrr$rrr;rs rrKz5VaeImageProcessorLDM3D.preprocess..]s)BBBt{{1fe44BBBrc>g|]}|SrNrr)s rrKz5VaeImageProcessorLDM3D.preprocess..^s)FFF1Q66FFFrr r]rrrF)!rrrrrrrr6rrrr&r'r:rr5r/rrarerrr`rr3rrrrrrmr4r)r;r"r#rrr$r3rs` `` @rrz!VaeImageProcessorLDM3D.preprocess=s[!Y_bj%,G ; + 9 3rz@Z0[0[ 9`c`hlm`m`m788 8 c, - - %CGEES$'' C/^/^/^/^Z]/^/^/^,^,^ E1G1G31G1G1GEEfjfofoqBgCgCEE  c!fcio . . 9{) = ;<<<{$ G  G\f v = =c!ffe T T Tlv BBBBBBcBBBFFFFFFFFF##C((C""3''C++E22E$$U++EE A + + 914Q1A1A".1----rxPSZ[G\G\G\C""3''C 99#vuMMMFE{$ 6kk#vu5558V[A5E5EBN5q111128TY`aKbKbKbE$$U++E 99%OOMFE{$ : E6599 A - - 9788 84{/ 7799q==\= M@gjgngngpgp@@svszszs|s|@@@    !L  *..%%CNN5))E ; " )--$$CMM%((EEzr)Tr-r.Tr)NNN)rrrrr rr rrrr9rrrrrrrVrrrrrrrrrrrs@rrrs  K !!!     RZ D,A   \  5cio)> )O#P UWU_   \ 65U\)A#B6uRZY^YeMeGf666\6RZD4I.!/3 5I5I|5I5I!d, 5I sy EL8 9 5I5I5I5Iv!%#$( aa 5<"*< =aU\39?BJ>?a a } a SM a aaaaaaaarrceZdZdZeZe ddedede d ed ed ef fd Z e d e j dededefdZxZS)IPAdapterMaskProcessora Image processor for IP Adapter image masks. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. vae_scale_factor (`int`, *optional*, defaults to `8`): VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor. resample (`str`, *optional*, defaults to `lanczos`): Resampling filter to use when resizing the image. do_normalize (`bool`, *optional*, defaults to `False`): Whether to normalize the image to [-1,1]. do_binarize (`bool`, *optional*, defaults to `True`): Whether to binarize the image to 0/1. do_convert_grayscale (`bool`, *optional*, defaults to be `True`): Whether to convert the images to grayscale format. Tr-r.Fr/r0r2r3r4r6cVt||||||dSN)r/r0r2r3r4r6r r;r/r0r2r3r4r6r<s rr9zIPAdapterMaskProcessor.__init__B -%#!5      rr batch_size num_queriesvalue_embed_dimc|jd}|jd}||z }ttj||z }t|t|t|zdkz}||z}t j|d||fdd} | jd|kr| |dd} | | jdd} ||z} | |krAtj dtt j | d|| jdz fd } | |kr(tj dt| d d d |f} | | jd| jdddd|} | S) a Downsamples the provided mask tensor to match the expected dimensions for scaled dot-product attention. If the aspect ratio of the mask does not match the aspect ratio of the output image, a warning is issued. Args: mask (`torch.Tensor`): The input mask tensor generated with `IPAdapterMaskProcessor.preprocess()`. batch_size (`int`): The batch size. num_queries (`int`): The number of queries. value_embed_dim (`int`): The dimensionality of the value embeddings. Returns: `torch.Tensor`: The downsampled mask tensor. r rrbicubic)rrGrBzThe aspect ratio of the mask does not match the aspect ratio of the output image. Please update your masks or adjust the output size for optimal performance.g)valueN)rSrmathsqrtFrrrJrepeatviewrr UserWarningr) rr1r2r3o_ho_wrmask_hmask_wmask_downsampledownsampled_areas r downsamplez!IPAdapterMaskProcessor.downsamples*jmjmc TY{U23344VsK#f++$=!#CDDD&-q(9(9@PW`aaaiijkll   #j 0 0-44ZAFFO)../DQ/GLL!F? k ) ) M^     eOaG\]^G_9_5`hklllO k ) ) M^    .aaa+o>O*../DQ/GI^_`Iacdeell q/  r)Tr-r.FTT)rrrrr rr rrrr9rrrrCrrs@rr,r,s&K !!" %)          #      $;;3;S;[^;;;\;;;;;rr,ceZdZdZe ddededed ed ed ef fd Ze d edede de eeffdZ e de jdedede jfdZxZS)PixArtImageProcessora Image processor for PixArt image resize and crop. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. Can accept `height` and `width` arguments from [`image_processor.VaeImageProcessor.preprocess`] method. vae_scale_factor (`int`, *optional*, defaults to `8`): VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor. resample (`str`, *optional*, defaults to `lanczos`): Resampling filter to use when resizing the image. do_normalize (`bool`, *optional*, defaults to `True`): Whether to normalize the image to [-1,1]. do_binarize (`bool`, *optional*, defaults to `False`): Whether to binarize the image to 0/1. do_convert_rgb (`bool`, *optional*, defaults to be `False`): Whether to convert the images to RGB format. do_convert_grayscale (`bool`, *optional*, defaults to be `False`): Whether to convert the images to grayscale format. Tr-r.Fr/r0r2r3r4r6cVt||||||dSr.r r/s rr9zPixArtImageProcessor.__init__r0rrrratiosr=ct||z t|fd}||}t|dt|dfS)z Returns binned height and width.cBtt|z Sr")absri)rars rz@PixArtImageProcessor.classify_height_width_bin..6sSuPRAR=S=Sr)keyrr )rirkeysr)rrrG closest_ratio default_hwrKs @rclassify_height_width_binz.PixArtImageProcessor.classify_height_width_bin2sg6E> " "FKKMM/S/S/S/STTT M* :a=!!3z!}#5#555rsamples new_width new_heightcV|jd|jd}}||ks||krt||z ||z }t||z}t||z}tj|||fdd}||z dz}||z} ||z dz} | |z} |dddd| | || f}|S)NrrbilinearF)rrG align_corners)rSrrr9r) rRrSrT orig_height orig_widthr resized_widthresized_heightstart_xend_xstart_yend_ys rresize_and_crop_tensorz+PixArtImageProcessor.resize_and_crop_tensor:s")-"2GM!4DZ  * $ $ i(?(? [0)j2HIIE U 233M u!455Nm~}=J^cG %y0Q6Gi'E% 2q8Gj(EaaaGEM75=@AGr)Tr-r.TFF)rrrrr rrrr9rdictrrQrrr`rrs@rrErE s1* !!!!%*          #      $6#6c646ERUWZRZO666\6 RUZ_Zf\rrE)$r7rtypingrrrrrjr PIL.Imagerrtorch.nn.functionalrrr9rrr configuration_utilsr r utilsr rrrrrPipelineDepthInputrr*r,rr,rErNrrrhs //////////// ,,,,,,,,,,@@@@@@@@<<<<<<<<<<IOJ L (xxx   q q q q q  q q q hnnnnn.nnnbeeeee.eeePGGGGG,GGGGGr