cCin&SrSSKJrJr SSKrSSKJrJr SSK J r J r J r SSK JrJrJrJrJrJrJrJr SSKJrJrJr SS KJr \R8"\5r"S S \5rS /r g) z"Image processor class for Swin2SR.)OptionalUnionN)BaseImageProcessor BatchFeature)get_image_sizepadto_channel_dimension_format)ChannelDimension ImageInputinfer_channel_dimension_formatis_scaled_imagemake_flat_list_of_imagesto_numpy_array valid_imagesvalidate_preprocess_arguments) TensorTypefilter_out_non_signature_kwargslogging)deprecate_kwargc^\rSrSrSrS/rSS\S\\\ 4S\S\SS 4 U4S jjjr \ S 5r \ RS 5r SS \RS\S\\\\4S\\\\44Sjjr\"5\"SSSS9S S S S S \R,S 4S\S\\S\\ S\\S\\S\\\\4S\\\4S\\\\44Sjj55rSrU=r$)Swin2SRImageProcessor(a Constructs a Swin2SR image processor. Args: do_rescale (`bool`, *optional*, defaults to `True`): Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by the `do_rescale` parameter in the `preprocess` method. rescale_factor (`int` or `float`, *optional*, defaults to `1/255`): Scale factor to use if rescaling the image. Can be overridden by the `rescale_factor` parameter in the `preprocess` method. pixel_values do_rescalerescale_factordo_pad size_divisorreturnNc >[TU]"S0UD6 XlX lX0lUR S5nUbX@lgUUlg)Npad_size)super__init__rrrgetr)selfrrrrkwargsr! __class__s n/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/swin2sr/image_processing_swin2sr.pyr$Swin2SRImageProcessor.__init__7sE "6"$, ::j),8,DL(cD[RS5 UR$Nzb`self.pad_size` attribute is deprecated and will be removed in v5. Use `self.size_divisor` insteadloggerwarningr)r&s r)r!Swin2SRImageProcessor.pad_sizeGs p    r+c:[RS5 Xlgr-r.)r&values r)r!r1Ns p "r+imagesize data_formatinput_data_formatcv[X5upVXR-S-U-U- nXb-S-U-U- n[USU4SU44SUUS9$)a> Pad an image to make the height and width divisible by `size`. Args: image (`np.ndarray`): Image to pad. size (`int`): The size to make the height and width divisible by. data_format (`str` or `ChannelDimension`, *optional*): The channel dimension format for the output image. If unset, the channel dimension format of the input image is used. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. input_data_format (`str` or `ChannelDimension`, *optional*): The channel dimension format for the input image. If unset, the channel dimension format is inferred from the input image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. Returns: `np.ndarray`: The padded image. r symmetric)moder6r7)rr ) r&r4r5r6r7 old_height old_width pad_height pad_widths r)r Swin2SRImageProcessor.padUsh:!/u H  (1,4zA &*d2Y>  _q)n -#/   r+r!v5)versionnew_nameimagesreturn_tensorsc UbUO URnUbUO URnUbUO URnUbUO URn[ U5n[ U5(d [ S5e[UUS9 UV s/sHn [U 5PM nn U(a([US5(a[RS5 Uc[US5nU(a UV s/sHn URXUS9PM nn U(aUV s/sHoRXUS9PM nn UV s/sH n [XUS9PM nn SU0n [!XS 9$s sn fs sn fs sn fs sn f) a Preprocess an image or batch of images. Args: images (`ImageInput`): Image to preprocess. Expects a single or batch of images with pixel values ranging from 0 to 255. If passing in images with pixel values between 0 and 1, set `do_rescale=False`. do_rescale (`bool`, *optional*, defaults to `self.do_rescale`): Whether to rescale the image values between [0 - 1]. rescale_factor (`float`, *optional*, defaults to `self.rescale_factor`): Rescale factor to rescale the image by if `do_rescale` is set to `True`. do_pad (`bool`, *optional*, defaults to `True`): Whether to pad the image to make the height and width divisible by `window_size`. size_divisor (`int`, *optional*, defaults to 32): The size of the sliding window for the local attention. return_tensors (`str` or `TensorType`, *optional*): The type of tensors to return. Can be one of: - Unset: Return a list of `np.ndarray`. - `TensorType.TENSORFLOW` or `'tf'`: Return a batch of typ, input_data_format=input_data_format `tf.Tensor`. - `TensorType.PYTORCH` or `'pt'`: Return a batch of type `torch.Tensor`. - `TensorType.NUMPY` or `'np'`: Return a batch of type `np.ndarray`. - `TensorType.JAX` or `'jax'`: Return a batch of type `jax.numpy.ndarray`. data_format (`ChannelDimension` or `str`, *optional*, defaults to `ChannelDimension.FIRST`): The channel dimension format for the output image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - Unset: Use the channel dimension format of the input image. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format for the input image. If unset, the channel dimension format is inferred from the input image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - `"none"` or `ChannelDimension.NONE`: image in (height, width) format. zkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.)rrrzIt looks like you are trying to rescale already rescaled images. If the input images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again.)r4scaler7)r5r7)input_channel_dimr)data tensor_type)rrrrrr ValueErrorrrrr/ warning_oncer rescaler r r) r&rDrrrrrEr6r7r4rIs r) preprocess Swin2SRImageProcessor.preprocess~s`$.#9Zt +9+E4K^K^!-4;;'3'?|TEVEV )&1F##:  &!) 6<vay I  $#E 5Rc d#  kqrkqbghhuK\h]kqFrou ntej 'N_ `nt  'BB5= s s9EE E!E)rrrr)Tgp?T)NN)__name__ __module__ __qualname____firstlineno____doc__model_input_namesboolrintfloatr$propertyr!setternpndarrayrstrr r rrFIRSTr rrN__static_attributes__ __classcell__)r(s@r)rr(s (( ,3 SSc5j)S S  S SS !! __""?CDH ' zz' ' eC)9$9:; ' $E#/?*?$@A ' R%&ZG&**.!%&*;?4D4J4JDHZCZCTNZC! ZC  ZC sm ZC!sJ!78ZC3 001ZC$E#/?*?$@AZCH'ZCr+r)!rUtypingrrnumpyr\image_processing_utilsrrimage_transformsrr r image_utilsr r r rrrrrutilsrrrutils.deprecationr get_loggerrQr/r__all__r"r+r)rksb)"FPP   JI0   H %rC.rCj # #r+