o i)B@sdZddlmZmZddlZddlmZmZm Z ddl m Z m Z m Z ddlmZmZmZmZmZmZmZmZmZddlmZmZmZmZeeZerPddl Z Gd d d eZ!d gZ"dS) z$Image processor class for Chameleon.)OptionalUnionN)BaseImageProcessor BatchFeature get_size_dict)get_resize_output_image_sizeresizeto_channel_dimension_format) ChannelDimension ImageInputPILImageResamplinginfer_channel_dimension_formatis_scaled_imagemake_flat_list_of_imagesto_numpy_array valid_imagesvalidate_preprocess_arguments) TensorTypefilter_out_non_signature_kwargsis_vision_availableloggingc#seZdZdZdgZddejjddddddddf dede e e e fde d ed e e e e fd ed ee efd ede eeeefde eeeefdeddffdd Ze jddfdejde e e fde de ee efde ee efdejf ddZeddddddddddddejdfdede ede e e e fde e d e ed e e d e ed e ed e ede eeeefde eeeefde ede ee efde ede ee efdejjf ddZdedefddZZS)ChameleonImageProcessora Constructs a Chameleon 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 `do_resize` in the `preprocess` method. size (`dict[str, int]` *optional*, defaults to `{"shortest_edge": 512}`): Size of the image after resizing. The shortest edge of the image is resized to size["shortest_edge"], with the longest edge resized to keep the input aspect ratio. Can be overridden by `size` in the `preprocess` method. resample (`PILImageResampling`, *optional*, defaults to 1): Resampling filter to use if resizing the image. Can be overridden by `resample` in the `preprocess` method. do_center_crop (`bool`, *optional*, defaults to `True`): Whether to center crop the image to the specified `crop_size`. Can be overridden by `do_center_crop` in the `preprocess` method. crop_size (`dict[str, int]` *optional*, defaults to {"height": 512, "width": 512}): Size of the output image after applying `center_crop`. Can be overridden by `crop_size` in the `preprocess` method. do_rescale (`bool`, *optional*, defaults to `True`): Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by `do_rescale` in the `preprocess` method. rescale_factor (`int` or `float`, *optional*, defaults to 0.0078): Scale factor to use if rescaling the image. Can be overridden by `rescale_factor` 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 `[1.0, 1.0, 1.0]`): 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 `[1.0, 1.0, 1.0]`): 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_valuesTNgq? do_resizesizeresampledo_center_crop crop_size do_rescalerescale_factor do_normalize image_mean image_stddo_convert_rgbreturnc  stjd i| |dur|nddi}t|dd}|dur|nddd}t|ddd}||_||_||_||_||_||_||_ ||_ | durI| ngd |_ | durT| ngd |_ | |_ dS) N shortest_edgeiF)default_to_square)heightwidthTr)r' param_name)?r+r+)super__init__rrrrrrrr r!r"r#r$) selfrrrrrrr r!r"r#r$kwargs __class__r,l/home/ubuntu/.local/lib/python3.10/site-packages/transformers/models/chameleon/image_processing_chameleon.pyr.Ts   z ChameleonImageProcessor.__init__image data_formatinput_data_formatc Ksnd}d|vr |d}d}nd|vrd|vr|d|df}ntdt||||d}t|f||||d|S) aZ Resize an image. The shortest edge of the image is resized to size["shortest_edge"], with the longest edge resized to keep the input aspect ratio. Args: image (`np.ndarray`): Image to resize. size (`dict[str, int]`): Size of the output image. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): Resampling filter to use when resiizing the image. data_format (`str` or `ChannelDimension`, *optional*): The channel dimension format of the image. If not provided, it will be the same as the input image. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format of the input image. If not provided, it will be inferred. Tr&Fr(r)zASize must contain either 'shortest_edge' or 'height' and 'width'.)rr'r6)rrr5r6) ValueErrorrr ) r/r4rrr5r6r0r' output_sizer,r,r3r vs.zChameleonImageProcessor.resizeimagesreturn_tensorsc s|dur|nj}|dur|nj}t|ddd}|dur|nj}|dur(|nj}|dur1|nj}t|ddd}|durA|nj}|durJ|nj}| durS| nj} | dur\| nj } | dure| nj } | durn| nj }  |}t |}t|stdt||| | | |||||d | rfd d |D}d d |D}|rt|d rtd durt|d g}|D]1}|rʈj|||d}|rԈj||d}|rވj||d}| rj|| | d}||qfdd |D}d|i}t|| dS)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`): Size of the image after resizing. Shortest edge of the image is resized to size["shortest_edge"], with the longest edge resized to keep the input aspect ratio. resample (`int`, *optional*, defaults to `self.resample`): Resampling filter to use if resizing the image. This can be one of the enum `PILImageResampling`. Only has an effect if `do_resize` is set to `True`. do_center_crop (`bool`, *optional*, defaults to `self.do_center_crop`): Whether to center crop the image. crop_size (`dict[str, int]`, *optional*, defaults to `self.crop_size`): Size of the center crop. Only has an effect if `do_center_crop` is set to `True`. do_rescale (`bool`, *optional*, defaults to `self.do_rescale`): Whether to rescale the image. 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 use for normalization. Only has an effect if `do_normalize` is set to `True`. image_std (`float` or `list[float]`, *optional*, defaults to `self.image_std`): Image standard deviation to use for normalization. Only has an effect 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. NrF)r*r'rTzkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.) rr r!r"r#rrrrrcsg|]}|qSr,) blend_rgba.0r4)r/r,r3 sz6ChameleonImageProcessor.preprocess..cSsg|]}t|qSr,)rr<r,r,r3r>srzIt 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.)r4rrr6)r4rr6)r4scaler6)r4meanstdr6csg|] }t|dqS))input_channel_dim)r r<)r5r6r,r3r>1s r)data tensor_type)rrrrrrrr r!r"r#r$ fetch_imagesrrr7rrlogger warning_oncerr center_croprescale normalizeappendr)r/r9rrrrrrr r!r"r#r$r:r5r6 all_imagesr4rCr,)r5r6r/r3 preprocessstF      z"ChameleonImageProcessor.preprocesscCst|tjjs |S|jdkr|St|d}|dddddfdks,|dS|dddddfd}d|ddddtjfd|ddddtjf|ddddddf}tj | ddS) a Convert image to RGB by blending the transparency layer if it's in RGBA format. If image is not `PIL.Image`, it si simply returned without modifications. Args: image (`ImageInput`): Image to convert. RGBRGBANrgo@uint8) isinstancePILImagemodenparrayconvertanynewaxis fromarrayastype)r/r4img_rgbaalphaimg_rgbr,r,r3r;9s   Rz"ChameleonImageProcessor.blend_rgba)__name__ __module__ __qualname____doc__model_input_namesrTrULANCZOSboolrdictstrintr rfloatlistr.BICUBICrWndarrayr r rFIRSTr rrMr; __classcell__r,r,r1r3r+s&     &  1      r)#rdtypingrrnumpyrWimage_processing_utilsrrrimage_transformsrr r image_utilsr r r rrrrrrutilsrrrr get_loggerrarFrTr__all__r,r,r,r3s,  ,