^jNddlZddlZddlZddlZddlmZmZmZmZddl Z ddl m Z ddl m cm Z ddl mZdZddlmZddlZgdZGdd ZGd d ZGd d e j0ZGddZeedrej8j:dej8j<dej8j>dej8j@dej8jBdej8jDdiZ#nJej:dej<dej>dej@dejBdejDdiZ#e#jIDcic]\}}|| c}}Z%eroej:dej<dej>dej@dejBdejDdiZ&e&jIDcic]\}}|| c}}Z'niZ(iZ&dZ)dZ*dZ+e*de*dfZ,d2dZ-GddZ. d3de j^dee0ee0fdee0ee0e0e0ffd e1d!e j^f d"Z2Gd#d$e jfjhZ5 d3de j^d%e0d&e0d'e0d(e0dee0ee0e0e0ffd e1d!e j^fd)Z6Gd*d+e jfjhZ7Gd,d-Z8Gd.d/Z9Gd0d1e jfjhZ:y#e$rdZYwxYwcc}}wcc}}w)4N)ListSequenceTupleUnion)InterpolationModeTF)Image)ToNumpyToTensorstr_to_interp_modestr_to_pil_interpinterp_mode_to_str!RandomResizedCropAndInterpolationCenterCropOrPadcenter_crop_or_pad crop_or_padRandomCropOrPad RandomPadResizeKeepRatio TrimBorder MaybeToTensorMaybePILToTensorceZdZdZy)r ctj|tj}|jdkrtj|d}tj |d}|S)Ndtype)axis)nparrayuint8ndim expand_dimsrollaxis)selfpil_imgnp_imgs _/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/timm/data/transforms.py__call__zToNumpy.__call__sF'2 ;;?^^F4FVQ' N)__name__ __module__ __qualname__r*r+r)r r sr+r c4eZdZdZej fdZdZy)r z% ToTensor with no rescaling of valuesc||_yNr)r&rs r)__init__zToTensor.__init__%s  r+c`tj|j|jS)Nr)F pil_to_tensortor)r&r's r)r*zToTensor.__call__(s#w'***<r@s r)r3zMaybePILToTensor.__init__GrBr+cdt|tjr|Stj|S)z Note: A deep copy of the underlying array is performed. Args: pic (PIL Image): Image to be converted to tensor. Returns: Tensor: Converted image. )rDr9rEr5r6rGs r)r*zMaybePILToTensor.__call__Js& c5<< (Js##r+c4|jjdSrJrKrLs r)rMzMaybePILToTensor.__repr__XrNr+rO) r,r-r.r8r3r*rPrMrQrRs@r)rrCs $.#.r+r Resamplingnearestbilinearbicubicboxhamminglanczosct|Sr2)_str_to_pil_interpolationmode_strs r)r r s $X ..r+c2tr t|St|Sr2)has_interpolation_mode_str_to_torch_interpolationr_r`s r)r r s*844(22r+c2tr t|St|Sr2)rc_torch_interpolation_to_str_pil_interpolation_to_str)modes r)r r s*400(..r+ct|tjrt|t|fSt|trt |dk(r |d|dfSt |dk7r t ||S)Nrr)rDnumbersNumberintrlen ValueError)size error_msgs r) _setup_sizerrse$'4y#d)##$!c$i1nAwQ 4yA~## Kr+c:eZdZdZ ddZedZdZdZy)raYCrop the given PIL Image to random size and aspect ratio with random interpolation. A crop of random size (default: of 0.08 to 1.0) of the original size and a random aspect ratio (default: of 3/4 to 4/3) of the original aspect ratio is made. This crop is finally resized to given size. This is popularly used to train the Inception networks. Args: size: expected output size of each edge scale: range of size of the origin size cropped ratio: range of aspect ratio of the origin aspect ratio cropped interpolation: Default: PIL.Image.BILINEAR ct|ttfrt||_n ||f|_|d|dkDs |d|dkDrt j d|dk(r t |_nt||_||_ ||_ y)Nrrjz"range should be of kind (min, max)random) rDlisttuplerpwarningswarn_RANDOM_INTERPOLATION interpolationr scaleratio)r&rpr|r}r{s r)r3z*RandomResizedCropAndInterpolation.__init__s dT5M *d DIt DI !HuQx U1Xa%8 MM> ? H $!6D !3M!BD   r+c ftj|\}}||z}tdD]}tj||z}t j |dt j |df}t jtj|} ttt j|| z} ttt j|| z } | |ks| |kstjd|| z } tjd|| z } | | | | fcS||z }|t|kr#|} tt| t|z } n5|t|kDr#|} tt| t|z} n|} |} || z dz} || z dz} | | | | fS)aGet parameters for ``crop`` for a random sized crop. Args: img (PIL Image): Image to be cropped. scale (tuple): range of size of the origin size cropped ratio (tuple): range of aspect ratio of the origin aspect ratio cropped Returns: tuple: params (i, j, h, w) to be passed to ``crop`` for a random sized crop. rrjr)r5get_image_sizerangeruuniformmathlogexprmroundsqrtrandintminmax)imgr|r}img_wimg_hareaattempt target_area log_ratio aspect_ratiotarget_wtarget_hijin_ratios r) get_paramsz,RandomResizedCropAndInterpolation.get_paramss'', uu}Ry 0G ..%047K%(+TXXeAh-?@I88FNNI$>?L5;+E!FGHH5;+E!FGHH5 X%6NN1eh&67NN1eh&67!Xx// 05= c%j H5CJ!678H E "H5CJ!678HHH X ! # X ! #!Xx''r+c <|j||j|j\}}}}t|jt t fr tj|j}n |j}tj||||||j|S)z Args: img (PIL Image): Image to be cropped and resized. Returns: PIL Image: Randomly cropped and resized image. ) rr|r}rDr{rwrvruchoicer5 resized_croprp)r&rrrhwr{s r)r*z*RandomResizedCropAndInterpolation.__call__sx__S$**djjA 1a d((5$- 8"MM$*<*<=M ..M~~c1aAtyy-HHr+c$t|jttfr3dj |jDcgc] }t |c}}nt |j}|j jdj|jz}|djtd|jDz }|djtd|jDz }|dj|z }|Scc}w)N (size={0}z , scale={0}c34K|]}t|dywNr).0ss r) z=RandomResizedCropAndInterpolation.__repr__.. 3TAE!QK3Tz , ratio={0}c34K|]}t|dywrr)rrs r)rz=RandomResizedCropAndInterpolation.__repr__.. rrz, interpolation={0})) rDr{rwrvjoinr rAr,formatrpr|r}r&xinterpolate_str format_strings r)rMz*RandomResizedCropAndInterpolation.__repr__s d((5$- 8!hhtGYGY'Z!(:1(='Z[O01C1CDO//+2D2DTYY2OO --e3T3T.TUU --e3T3T.TUU /66GG ([sD N))g{Gz??)g?gUUUUUU?rY r,r-r.r8r3 staticmethodrr*rMr/r+r)rrs7 "$$ *((((T I r+rr output_sizefill padding_moder<ct|}|\}}tj|\}}}||kDs||kDr~||kDr||z dznd||kDr||z dznd||kDr ||z dzdznd||kDr ||z dzdzndg} tj|| ||}tj|\}}}||k(r||k(r|St t ||z dz } t t ||z dz } tj || | ||S)akCenter crops and/or pads the given image. If the image is torch Tensor, it is expected to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions. If image size is smaller than output size along any edge, image is padded with 0 and then center cropped. Args: img (PIL Image or Tensor): Image to be cropped. output_size (sequence or int): (height, width) of the crop box. If int or sequence with single int, it is used for both directions. fill (int, Tuple[int]): Padding color Returns: PIL Image or Tensor: Cropped image. rrrjrrg@)rrr5get_dimensionspadrmrcrop) rrrr crop_height crop_width_ image_height image_width padding_ltrbcrop_top crop_lefts r)rrs4*k*K)K#$#3#3C#8 A|[K;#=/9K/GZ+ %! +Q1<|1K[< 'A -QR3= 3KZ+ % )a /QR5@<5O[< '! + 1UV  eeCD|L'('7'7'<$<  $ )DJ5,4;<=HE;3s:;#>r+rtopleftheightwidthc tj|\}}} ||z} ||z} |dks|dks | | kDs| |kDr}t| td| zdt| td| zdt| t| |z dt| t||z dg} tj|| ||}t|d}t|d}tj |||||S)z[ Crops and/or pads image to meet target size, with control over fill and padding_mode. rr)r5rrrrr) rrrrrrrrrrrightbottomrs r)rr_s$%#3#3C#8 A|[ 5LE 6\F ax37ek1Vl5J Au %q ) s1f~%q ) K.. 2 \3// 3  eeCD|L c1+C tQ#>r+rc*eZdZddZedZdZy)rc ||_||_yr2) input_sizer)r&rrs r)r3zRandomPad.__init__s$ r+ctj|\}}t|d|z d}t|d|z d}tjd|}tjd|}||z }||z } |||| fS)Nrjr)r5rrrur) rrrrrrpad_leftpad_top pad_right pad_bottoms r)rzRandomPad.get_paramss((- v*Q-%/3 :a=6115 >>![1..L1(* !G+ )Z77r+c|j||j}tj|||j}|Sr2)rrr5rr)r&rpaddings r)r*zRandomPad.__call__s1//#t7eeC$)), r+N)r)r,r-r.r3rrr*r/r+r)rrs 88r+rcNeZdZdZ ddZe ddZdZdZy) rz" Resize and Keep Aspect Ratio c  t|ttfrt||_n ||f|_|dk(r t|_nt ||_t||_||_ ||_ ||_ ||_ ||_ y)z Args: size: longest: interpolation: random_scale_prob: random_scale_range: random_scale_area: random_aspect_prob: random_aspect_range: ruN)rDrvrwrprzr{r floatlongestrandom_scale_probrandom_scale_rangerandom_scale_arearandom_aspect_probrandom_aspect_range) r&rprr{rrrrrs r)r3zResizeKeepRatio.__init__sx. dT5M *d DIt DI H $!6D !3M!BD W~ !2"4!2"4#6 r+ctj|ddx\}} } |\} } || z } | | z }t| ||zt| |d|z zz}|dkDrRt j|kr;t j |d|d}|rdt j|z }||f}nd}|dkDrt j|krzt j|dt j|df}t jt j |}t j|}|d|z |d|zf}t| |Dcgc]\}}t||z|z }}}|Scc}}w)zGet parameters rjNrr)rr) r5rrrrurrrrrzipr)r target_sizerrrrrrrrimg_sizerrratio_hratio_wr} ratio_factor log_aspect aspect_factorrfrps r)rzResizeKeepRatio.get_paramss{#$"2"23"7";; ux((("("GW%/#gw2G2PW<2XX q V]]_7H%H!>>*r sc  // +--#C! ==.J''....8 5,   ) !!:   ) e   )   ) !  y   y 5 y y !/H.M.M.OPdaQTP!!9""J!!9u!!9!!9 #5P4U4U4W"XDAq1a4"X"$"$/3/,J79KI9VW ggZ23& 'E \\'E3S >*'ECsC}--.'E 'E  \\ 'ET">ehhoo">V23&1 \\1 11 1  1 CsC}--. 11 \\18,>ehhoo,>^,ttn55U#"#JQ#YsK4' L L4K?>K?