cCi^SrSSKJrJr SSKrSSKJrJrJ r SSK J r J r J r JrJr SSKJrJrJrJrJrJrJrJrJrJrJrJr SSKJrJrJ r SS K!J"r" \ RF"\$5r%\""5(aSSK&r&"S S \5r'S /r(g) z!Image processor class for Nougat.)OptionalUnionN)BaseImageProcessor BatchFeature get_size_dict)get_resize_output_image_sizepadresizeto_channel_dimension_format to_pil_image) IMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STDChannelDimension ImageInputPILImageResamplingget_image_sizeinfer_channel_dimension_formatis_scaled_imagemake_flat_list_of_imagesto_numpy_array valid_imagesvalidate_preprocess_arguments) TensorTypefilter_out_non_signature_kwargslogging)is_vision_availablec%^\rSrSrSrS/rSSS\RSSSSSSSS4 S\S \S \ \ \ \ 4S \S \S \S\S\S\ \ \4S\S\ \ \\\4S\ \ \\\4SS4U4SjjjrS\R$4SjrSrS%S\R$S\ S\ \S\ \ \ \4S\R$4 SjjrS&S\R$S \ \ \ 4S\ \ \ \4S\ \ \ \4S\R$4 SjjrS&S\R$S \ \ \ 4S\ \ \ \4S\ \ \ \4S\R$4 Sjjr\R2SS4S\R$S \ \ \ 4S \S\ \ \ \4S\ \ \ \4S\R$4 Sjjr\R2SS4S\R$S \ \ \ 4S \S\ \ \ \4S\ \ \ \4S\R$4 S jjr\"5SSSSSSSSSSSSS\R:S4S!\S\ \S \ \S \ \ \ \ 4S \ \S \ \S \ \S\ \S\ \S\ \ \ \4S\ \S\ \ \\\4S\ \ \\\4S"\ \ \ \4S\ \S\ \ \ \4S\ RBRB4"S#jj5r"S$r#U=r$$)'NougatImageProcessor6a Constructs a Nougat image processor. Args: do_crop_margin (`bool`, *optional*, defaults to `True`): Whether to crop the image margins. do_resize (`bool`, *optional*, defaults to `True`): Whether to resize the image's (height, width) dimensions to the specified `size`. Can be overridden by `do_resize` in the `preprocess` method. size (`dict[str, int]` *optional*, defaults to `{"height": 896, "width": 672}`): Size of the image after resizing. Can be overridden by `size` in the `preprocess` method. resample (`PILImageResampling`, *optional*, defaults to `Resampling.BILINEAR`): Resampling filter to use if resizing the image. Can be overridden by `resample` in the `preprocess` method. do_thumbnail (`bool`, *optional*, defaults to `True`): Whether to resize the image using thumbnail method. do_align_long_axis (`bool`, *optional*, defaults to `False`): Whether to align the long axis of the image with the long axis of `size` by rotating by 90 degrees. do_pad (`bool`, *optional*, defaults to `True`): Whether to pad the images to the largest image size in the batch. do_rescale (`bool`, *optional*, defaults to `True`): Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by the `do_rescale` parameter in the `preprocess` method. rescale_factor (`int` or `float`, *optional*, defaults to `1/255`): Scale factor to use if rescaling the image. Can be overridden by the `rescale_factor` parameter in the `preprocess` method. do_normalize (`bool`, *optional*, defaults to `True`): Whether to normalize the image. Can be overridden by `do_normalize` in the `preprocess` method. image_mean (`float` or `list[float]`, *optional*, defaults to `IMAGENET_DEFAULT_MEAN`): Mean to use if normalizing the image. This is a float or list of floats the length of the number of channels in the image. Can be overridden by the `image_mean` parameter in the `preprocess` method. image_std (`float` or `list[float]`, *optional*, defaults to `IMAGENET_DEFAULT_STD`): Image standard deviation. pixel_valuesTNFgp?do_crop_margin do_resizesizeresample do_thumbnaildo_align_long_axisdo_pad do_rescalerescale_factor do_normalize image_mean image_stdreturnc  >[TU]"S0U D6 UbUOSSS.n[U5nXlX lX0lX@lXPlX`lXpl Xl Xl Xl U bU O[UlU bXlg[Ulg)Nii)heightwidth)super__init__rr"r#r$r%r&r'r(r)r*r+rr,rr-)selfr"r#r$r%r&r'r(r)r*r+r,r-kwargs __class__s l/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/nougat/image_processing_nougat.pyr4NougatImageProcessor.__init__[s "6"'tc-JT","  ("4 $,((2(>*DY&/&;AUimagec[R"[R"U55nUSS2SS/4nURSSS5nU$)zGThis is a reimplementation of a findNonZero function equivalent to cv2.Nr)np column_stacknonzeroreshape)r5r;non_zero_indicesidxvecs r8python_find_non_zero)NougatImageProcessor.python_find_non_zero}sC??2::e+<=!!aV),Aq) r:c[R"USS9R[5n[R"USS9R[5nUSUSpTUSU- S-nUSU- S-nXEXg4$)zHThis is a reimplementation of a BoundingRect function equivalent to cv2.rr=)axisrr=)r@minastypeintmax)r5 coordinates min_values max_valuesx_miny_minr1r0s r8python_bounding_rect)NougatImageProcessor.python_bounding_rectsxVVKf5<u E UHxx c*+22288<((*((*  HHUOE/JZJ_J_`E*,E@QR  L  L7#45;$**40&*&?&?&G#e E%-HI&&rxx0+EFVF[F[\S^Ri 'u E   0 5 5 5H "2"8"8 8H89J8KLM M  ([-G  ([-GHHUAH5E  "/VghE r:c~USUSpe[XS9upxXh- n XW- n U S-n U S-n X- n X- nX4X44n[XX4S9$)a' Pad the image to the specified size at the top, bottom, left and right. Args: image (`np.ndarray`): The image to be padded. size (`dict[str, int]`): The size `{"height": h, "width": w}` to pad the image to. data_format (`str` or `ChannelDimension`, *optional*): The data format of the output image. If unset, the same format as the input image is used. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format of the input image. If not provided, it will be inferred. r0r1rjr?)rWrX)rr )r5r;r$rWrXrtrurrrs delta_width delta_heightpad_toppad_left pad_bottom pad_rightpaddings r8 pad_imageNougatImageProcessor.pad_imagesq('+8nd7m|$25$X! "0 $3 !#!#!+ * (8*?@5{``r:c [XS9upxUSUSp[Xy5n [X5n X:XaX:XaU$Xx:a[X-U- 5n OX:a[X|-U- 5n [U4X4USUUS.UD6$)a Resize the image to make a thumbnail. The image is resized so that no dimension is larger than any corresponding dimension of the specified size. Args: image (`np.ndarray`): The image to be resized. size (`dict[str, int]`): The size `{"height": h, "width": w}` to resize the image to. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): The resampling filter to use. data_format (`Optional[Union[str, ChannelDimension]]`, *optional*): The data format of the output image. If unset, the same format as the input image is used. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format of the input image. If not provided, it will be inferred. rjr0r1g@)r$r% reducing_gaprWrX)rrKrMr ) r5r;r$r%rWrXr6rrrsrtrur0r1s r8 thumbnailNougatImageProcessor.thumbnails2%35$X! &*8nd7m|\1K.  !e&:L  % ,|;vay I  `fg`fW\d&&u@Q&R`fFg ouvoufkd**5tO`*aouFv $#E %dYj k#  ouvoufkdnn5tO`naouFv ouvoufkdnn5tO`naouFv $#E 5Rc d#  $#EU^op#  ou ntej '{N_ `nt  '>BB_=hw ww   s6J)J#J(8J- J2J70J<K9K) r'r"r+r(r)r#r&r,r-r%r*r$)NN)NN)%__name__ __module__ __qualname____firstlineno____doc__model_input_namesrBILINEARboolrdictstrrMrfloatlistr4r@ndarrayrFrTrrgrwrBICUBICrr rrorrPILImager__static_attributes__ __classcell__)r7s@r8rr6s D(( $)-'9'B'B!#(,3!:>9= V V VtCH~& V % V  V! V V Vc5j) V VU5$u+#567 VE%e"456 V  V VD"**+"26DH 2zz22./ 2 $E#/?*?$@A 2  2r?CDH -zz-38n-eC)9$9:; - $E#/?*?$@A -  -f?CDH !azz!a38n!aeC)9$9:; !a $E#/?*?$@A !a  !aP(:'A'A>BDH 0 zz0 38n0 % 0 eC)9$9:; 0 $E#/?*?$@A 0  0 n(:'A'A>BDH %zz%38n%% % eC)9$9:; % $E#/?*?$@A % %N%&*.$()-15'+-1!%%)6:'+:>9=;?2B2H2HDH#UCUC!UCD> UC tCH~& UC -. 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