`i^dZddlmZmZddlZddlmZmZm Z ddl m Z m Z m Z mZmZddlmZmZmZmZmZmZmZmZmZmZmZmZddlmZmZm Z dd l!m"Z"e j#e$Z%e"rddl&Z&Gd d eZ'd gZ(dS) z!Image processor class for Nougat.)OptionalUnionN)BaseImageProcessor BatchFeature get_size_dict)get_resize_output_image_sizepadresizeto_channel_dimension_format to_pil_image) IMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STDChannelDimension ImageInputPILImageResamplingget_image_sizeinfer_channel_dimension_formatis_scaled_imagemake_flat_list_of_imagesto_numpy_array valid_imagesvalidate_preprocess_arguments) TensorTypefilter_out_non_signature_kwargslogging)is_vision_availablec%heZdZdZdgZdddejddddddddf deded ee e e fd ed ed ed edede e e fdedee e ee fdee e ee fddffd ZdejfdZdZ d$dejde deedee e efdejf dZ d%dejd e e e fdee e efdee e efdejf dZ d%dejd e e e fdee e efdee e efdejf dZejddfdejd e e e fd edee e efdee e efdejf dZejddfdejd e e e fd edee e efdee e efdejf d Zedddddddddddddejdfd!edeedeed ee e e fd eed eed eed eedeedee e e fdeedee e ee fdee e ee fd"ee e efdeedee e efdej j f"d#Z!xZ"S)&NougatImageProcessora 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  6tjdi| ||nddd}t|}||_||_||_||_||_||_||_ ||_ | |_ | |_ | | nt|_| | nt|_dS)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 /home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/transformers/models/nougat/image_processing_nougat.pyr3zNougatImageProcessor.__init__[s ""6"""'ttc-J-JT"","   ("4 $,((2(>**DY&/&;AUimagectjtj|}|ddddgf}|ddd}|S)zGThis is a reimplementation of a findNonZero function equivalent to cv2.Nr)np column_stacknonzeroreshape)r4r9non_zero_indicesidxvecs r7python_find_non_zeroz)NougatImageProcessor.python_find_non_zero}sL?2:e+<+<==!!!!aV),Aq)) r8ctj|dt}tj|dt}|d|d}}|d|z dz}|d|z dz}||||fS)zHThis is a reimplementation of a BoundingRect function equivalent to cv2.rr;)axisrr;)r>minastypeintmax)r4 coordinates min_values max_valuesx_miny_minr0r/s r7python_bounding_rectz)NougatImageProcessor.python_bounding_rectsVKf555<arrayconvertrIuint8rKrHr rLASTrDrQcrop)r4r9rSrTrUdatamax_valmin_valgraycoordsrOrPr0r/s r7 crop_marginz NougatImageProcessor.crop_margins,  $ >u E E U6GHHHx c**++2228<<((**((** g  HUOOE/7HJZJ_``E*,E;@QRRR  Lw7W#45;n$**400&*&?&?&G&G#ueV E5%%-HII&&rx00+E3DFVF[\\S^Ri '{rot90r ) r4r9r#rTrU input_height input_width output_height output_widthrot_axess r7align_long_axisz$NougatImageProcessor.align_long_axiss.%35FW$X$X$X! k&*8nd7m|  $ >u E E   0 5 5 5HH "2"8 8 8HHL9JLLMM M = ( ([<-G-G = ( ([<-G-GHUAH555E  "/{VghhhE r8c|d|d}}t||\}}||z } ||z } | dz} | dz} | | z } | | z }| | f| |ff}t||||S)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. r/r0rfr=)rTrU)rr )r4r9r#rTrUrprqrnro delta_width delta_heightpad_toppad_left pad_bottom pad_rightpaddings r7 pad_imagezNougatImageProcessor.pad_images('+8nd7m| $25FW$X$X$X! k"[0 $|3 !#!#!G+ (* Z(8Y*?@5'{N_````r8c >t||\}}|d|d} } t|| } t|| } | |kr| |kr|S||krt|| z|z } n||krt|| z|z } t|f| | f|d||d|S)as Resize the image to make a thumbnail. The image is resized so that no dimension is larger than any corresponding dimension of the specified size. Args: image (`np.ndarray`): The image to be resized. size (`dict[str, int]`): The size `{"height": h, "width": w}` to resize the image to. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): The resampling filter to use. data_format (`Optional[Union[str, ChannelDimension]]`, *optional*): The data format of the output image. If unset, the same format as the input image is used. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format of the input image. If not provided, it will be inferred. rfr/r0g@)r#r$ reducing_gaprTrU)rrHrJr ) r4r9r#r$rTrUr5rnrorprqr/r0s r7 thumbnailzNougatImageProcessor.thumbnails2%35FW$X$X$X! k&*8nd7m| \=11K.. \ ! !e{&:&:L + % % f,|;<z3NougatImageProcessor.preprocess..s <<g|]}|S)rW)rd)rr9rUr4s r7rz3NougatImageProcessor.preprocess..s.gggW\d&&u@Q&RRgggr8c@g|]}|S))r#rU)rsrr9rUr4r#s r7rz3NougatImageProcessor.preprocess..s0vvvfkd**5tO`*aavvvr8cBg|]}|S))r9r#r$rU)r )rr9rUr$r4r#s r7rz3NougatImageProcessor.preprocess..s> %dXYj kkr8c@g|]}|S)r9r#rU)rrs r7rz3NougatImageProcessor.preprocess..-vvvfkdnn5tO`naavvvr8c@g|]}|Sr)r|rs r7rz3NougatImageProcessor.preprocess..rr8c@g|]}|S))r9scalerU)rescale)rr9rUr)r4s r7rz3NougatImageProcessor.preprocess..s< 5Rc ddr8cBg|]}|S))r9meanstdrU) normalize)rr9r+r,rUr4s r7rz3NougatImageProcessor.preprocess..s>U^oppr8c4g|]}t|S)ri)r )rr9rTrUs r7rz3NougatImageProcessor.preprocess..s7   ej '{N_ ` ` `   r8r )r_ tensor_type)r!r"r#r$r%r&r'r(r)r*r+r,rrrlrrlogger warning_oncerr)r4rr!r"r#r$r%r&r'r(r)r*r+r,rrTrUr_s` `` ` `` `` r7 preprocesszNougatImageProcessor.preprocessosLN,:+E4K^!*!6IIDN 'ttTY'388'3'?||TEV 3E3Q//W[Wn!-4;#-#9ZZt +9+E4K^'3'?||TEV #-#9ZZt !*!6IIDN )&11F## :  &!)%! =vay I I   hggggg`fgggF  wvvvvvvouvvvF  #F  wvvvvvvouvvvF  wvvvvvvouvvvF  #F  #F      nt   '>BBBBr8)rRNN)NN)#__name__ __module__ __qualname____doc__model_input_namesrBILINEARboolrdictstrrJrfloatlistr3r>ndarrayrDrQrrdrsr|BICUBICrr rrkrrPILImager __classcell__)r6s@r7rr6s  D(( $)-'9'B!#(,3!:>9= V V V VtCH~& V % V  V! V V Vc5j) V VU5$u+#567 VE%e"456 V  V V V V V VD"*+++"26DH 22z22./ 2 $E#/?*?$@A 2  2222r?CDH --z-38n-eC)9$9:; - $E#/?*?$@A -  ----f?CDH !a!az!a38n!aeC)9$9:; !a $E#/?*?$@A !a  !a!a!a!aP(:'A>BDH 0 0 z0 38n0 % 0 eC)9$9:; 0 $E#/?*?$@A 0  0 0 0 0 n(:'A>BDH %%z%38n%% % eC)9$9:; % $E#/?*?$@A % %%%%N%$&&*.$()-15'+-1!%%)6:'+:>9=;?2B2HDH#UCUCUC!UCD> UC tCH~& UC -. UCtnUC%TNUCUCTNUC!sEz!23UCtnUCU5$u+#567UCE%e"456UC!sJ!78UC ./!UC"$E#/?*?$@A#UC$ %UCUCUC'&UCUCUCUCUCr8r))rtypingrrnumpyr>image_processing_utilsrrrimage_transformsr r r r r image_utilsrrrrrrrrrrrrutilsrrrutils.import_utilsr get_loggerrrrr__all__r1r8r7rs('""""""""UUUUUUUUUU                            JIIIIIIIII555555  H % %JJJOCOCOCOCOC-OCOCOCd " "r8