+hfASrSSKJrJrJrJr SSKrSSKrSSK J r J r J r SSK JrJrJr SSKJrJrJrJrJrJrJrJrJrJr SSKJrJrJr SSK J!r! \"5(aSSK"r#\RH"\%5r&"S S \ 5r'g) zImage processor class for BLIP.)DictListOptionalUnionN)BaseImageProcessor BatchFeature get_size_dict)convert_to_rgbresizeto_channel_dimension_format) OPENAI_CLIP_MEANOPENAI_CLIP_STDChannelDimension ImageInputPILImageResamplinginfer_channel_dimension_formatis_scaled_imagemake_list_of_imagesto_numpy_array valid_images) TensorTypeis_vision_availablelogging) numpy_to_pilc ^\rSrSrSrS/rSS\RSSSSSSS4 S\S\ \ \ 4S \S \S \ \ \ 4S \S \\ \ \\ 4S\\ \ \\ 4S\S\SS4U4Sjjjr\RSS4S\R$S\ \ \ 4S \S\\ \ \4S\\ \ \4S\R$4 SjjrSSSSSSSSSSS\R*S4 S\S\\S\\ \ \ 4S \S \\S\\S \\ S \\S \\ \ \\ 4S\\ \ \\ 4S\\ \ \4S\S\S\\ \ \4S\R2R24SjjrSS\R8S\ 4SjjrSrU=r$)BlipImageProcessor1ad Constructs a BLIP image processor. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to resize the image's (height, width) dimensions to the specified `size`. Can be overridden by the `do_resize` parameter in the `preprocess` method. size (`dict`, *optional*, defaults to `{"height": 384, "width": 384}`): Size of the output image after resizing. Can be overridden by the `size` parameter in the `preprocess` method. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): Resampling filter to use if resizing the image. Only has an effect if `do_resize` is set to `True`. Can be overridden by the `resample` parameter in the `preprocess` method. do_rescale (`bool`, *optional*, defaults to `True`): Wwhether 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. Only has an effect if `do_rescale` is set to `True`. 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 the `do_normalize` parameter in the `preprocess` method. Can be overridden by the `do_normalize` parameter in the `preprocess` method. image_mean (`float` or `List[float]`, *optional*, defaults to `IMAGENET_STANDARD_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. Can be overridden by the `image_mean` parameter in the `preprocess` method. image_std (`float` or `List[float]`, *optional*, defaults to `IMAGENET_STANDARD_STD`): Standard deviation 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_std` parameter in the `preprocess` method. Can be overridden by the `image_std` parameter in the `preprocess` method. do_convert_rgb (`bool`, *optional*, defaults to `True`): Whether to convert the image to RGB. pixel_valuesTNgp? do_resizesizeresample do_rescalerescale_factor do_normalize image_mean image_stddo_convert_rgbdo_center_cropreturnc  >[T U]"S0U D6 UbUOSSS.n[USS9nXlX lX0lX@lXPlX`lUbUO[Ul UbUO[Ul Xl Xlg)N)heightwidthTdefault_to_square)super__init__r rr r!r"r#r$r r%rr&r'r() selfrr r!r"r#r$r%r&r'r(kwargs __class__s r/home/james-whalen/.local/lib/python3.13/site-packages/diffusers/pipelines/blip_diffusion/blip_image_processing.pyr2BlipImageProcessor.__init__Vs{ "6"'tc-JTT:"  $,((2(>*DT&/&;,,image data_formatinput_data_formatc [U5nSU;dSU;a[SUR535eUSUS4n[U4UUUUS.UD6$)a Resize an image to `(size["height"], size["width"])`. Args: image (`np.ndarray`): Image to resize. size (`Dict[str, int]`): Dictionary in the format `{"height": int, "width": int}` specifying the size of the output image. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): `PILImageResampling` filter to use when resizing the image e.g. `PILImageResampling.BICUBIC`. data_format (`ChannelDimension` or `str`, *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. - `"none"` or `ChannelDimension.NONE`: image in (height, width) format. 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. Returns: `np.ndarray`: The resized image. r,r-zFThe `size` dictionary must contain the keys `height` and `width`. Got )r r!r:r;)r ValueErrorkeysr )r3r9r r!r:r;r4 output_sizes r6r BlipImageProcessor.resizetsyFT" 4 7$#6efjfofofqerst tH~tG}5   #/     r8imagesreturn_tensorsc UbUO URnUbUO URnUbUO URnUbUO URnUbUO URnU bU O UR n U bU O UR n U bU O URn UbUO URnUbUO URn[USS9n[U5n[U5(d [S5eU(aUbUc [S5eU(aUc [S5eU(aU bU c [S5eU (aUVs/sHn[U5PM nnUVs/sHn[U5PM nn[!US5(aU(a["R%S5 Uc['US5nU(a!UVs/sHnUR)UX4US 9PM nnU(a UVs/sHnUR+UX~S 9PM nnU(a!UVs/sHnUR-UXUS 9PM nnU(a UVs/sHnUR/UX>S 9PM nnUVs/sH n[1UXS 9PM nn[3SU0U S9nU$s snfs snfs snfs snfs snfs snfs snf)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_resize (`bool`, *optional*, defaults to `self.do_resize`): Whether to resize the image. size (`Dict[str, int]`, *optional*, defaults to `self.size`): Controls the size of the image after `resize`. The shortest edge of the image is resized to `size["shortest_edge"]` whilst preserving the aspect ratio. If the longest edge of this resized image is > `int(size["shortest_edge"] * (1333 / 800))`, then the image is resized again to make the longest edge equal to `int(size["shortest_edge"] * (1333 / 800))`. resample (`PILImageResampling`, *optional*, defaults to `self.resample`): Resampling filter to use if resizing the image. Only has an effect if `do_resize` is set to `True`. 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_normalize (`bool`, *optional*, defaults to `self.do_normalize`): Whether to normalize the image. image_mean (`float` or `List[float]`, *optional*, defaults to `self.image_mean`): Image mean to normalize the image by if `do_normalize` is set to `True`. image_std (`float` or `List[float]`, *optional*, defaults to `self.image_std`): Image standard deviation to normalize the image by if `do_normalize` is set to `True`. do_convert_rgb (`bool`, *optional*, defaults to `self.do_convert_rgb`): Whether to convert the image to RGB. 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 type `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. Fr.zkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.z9Size and resample must be specified if do_resize is True.z7Rescale factor must be specified if do_rescale is True.z=Image mean and std must be specified if do_normalize is True.rzIt 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.)r9r r!r;)r9scaler;)r9meanstdr;)r;)input_channel_dimr)data tensor_type)rr!r"r#r$r%r&r'r(r r rrr=r rrlogger warning_oncerr rescale normalize center_cropr r)r3rArr r!r"r(r#r$r%r&rBr'r:r;r4r9encoded_outputss r6 preprocessBlipImageProcessor.preprocesssB"+!6IDNN '38#-#9Zt +9+E4K^K^'3'?|TEVEV #-#9Zt !*!6IDNN +9+E4K^K^+9+E4K^K^'tTYYTU;$V,F##:  )9XY Y .0VW W Z/93D\] ] 9?@nU+F@6<vay I  $#E %dYj k#  $#E 5 d#  $#EU^op#  flmfl]bd&&ud&XflFmou ntej '{ `nt  '^V,DR`aMA=   n s*+I#I((I-I27I7I<?Jsample output_typecUS;a[SUS35eUS- S-RSS5nUS:XaU$UR5RSSS S5R 5nUS :XaU$[ U5nU$) N)ptnppilz output_type=zD is not supported. Make sure to choose one of ['pt', 'np', or 'pil']g?rrUrV)r=clampcpupermutenumpyr)r3rRrSs r6 postprocessBlipImageProcessor.postprocess-s 1 1{m+op  1*s"))!Q/ $ M%%aAq1779 $ Mf% r8) r(r'r$r"rr%r&r!r#r )rW) __name__ __module__ __qualname____firstlineno____doc__model_input_namesrBICUBICboolrstrintrfloatrrr2rVndarrayrr FIRSTrrPILImagerPtorchTensorr___static_attributes__ __classcell__)r5s@r6rr1s D((#'9'A'A,3!:>9=##--38n-% -  - c5j) --U5$u+#567-E%e"456--- --D(:'A'A>BDH . zz. 38n. % . eC)9$9:; . $E#/?*?$@A .  . f%))-'+%))-*.'+:>9=;?#(8(>(>DHFFD>FtCH~& F % F TN F!F!FtnFU5$u+#567FE%e"456F!sJ!78FF&F$E#/?*?$@AF" #FR%,,Sr8r)(retypingrrrrr^rVrp#transformers.image_processing_utilsrrr transformers.image_transformsr r r transformers.image_utilsr rrrrrrrrrtransformers.utilsrrrdiffusers.utilsr PIL.Imagern get_loggerrarJrr0r8r6r|sl&.. __]]   HG(   H % M+Mr8