
    sg]D                         d Z ddlmZmZmZmZ ddlZddlm	Z	m
Z
mZ ddlmZmZmZ ddlmZmZmZmZmZmZmZmZmZ ddlmZmZmZmZ  ej>                  e       Z! e       rddl"Z"d	eee      fd
Z# G d de	      Z$y)z$Image processor class for Chameleon.    )DictListOptionalUnionN   )BaseImageProcessorBatchFeatureget_size_dict)get_resize_output_image_sizeresizeto_channel_dimension_format)	ChannelDimension
ImageInputPILImageResamplinginfer_channel_dimension_formatis_scaled_imageis_valid_imageto_numpy_arrayvalid_imagesvalidate_preprocess_arguments)
TensorTypefilter_out_non_signature_kwargsis_vision_availableloggingreturnc                 D   t        | t        t        f      rCt        | d   t        t        f      r*t        | d   d         r| D cg c]  }|D ]  }|  c}}S t        | t        t        f      rt        | d         r| S t        |       r| gS t	        d|        c c}}w )a  
    Accepts images in list or nested list format, and makes a list of images for preprocessing.

    Args:
        images (`Union[List[List[ImageInput]], List[ImageInput], ImageInput]`):
            The input image.

    Returns:
        list: A list of images.
    r   z"Could not make batched video from )
isinstancelisttupler   
ValueError)imagesimg_listimgs      k/var/www/html/venv/lib/python3.12/site-packages/transformers/models/chameleon/image_processing_chameleon.pymake_batched_imagesr%   /   s     &4-(Zq	D%=-QVdeklmenopeqVr$*?h?s???	FT5M	*~fQi/H		x
9&B
CC @s   Bc            #           e Zd ZdZdgZddej                  j                  ddddddddfdede	e
ef   ded	ed
e	e
ef   dedeeef   dedeeeee   f      deeeee   f      deddf fdZej$                  ddfdej(                  de	e
ef   dedeee
ef      deee
ef      dej(                  fdZ e       ddddddddddddej0                  dfdedede	e
ef   ded	ed
ededededeeeee   f      deeeee   f      dedeee
ef      dee   deee
ef      dej                  j                  f d       ZdedefdZ xZS )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_resizesizeresampledo_center_crop	crop_size
do_rescalerescale_factordo_normalize
image_mean	image_stddo_convert_rgbr   c                 .   t        |   d
i | ||nddi}t        |d      }||nddd}t        |dd      }|| _        || _        || _        || _        || _        || _        || _	        || _
        |	|	ng d	| _        |
|
ng d	| _        || _        y )Nshortest_edgei   F)default_to_square)heightwidthTr-   )r6   
param_name)      ?r:   r:    )super__init__r
   r)   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   )selfr)   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   kwargs	__class__s                r$   r=   z ChameleonImageProcessor.__init__o   s     	"6"'tos-CTU;!*!6IsUX<Y	!)tP[\	"	 ,"$,((2(>*O&/&;,    imagedata_formatinput_data_formatc                     d}d|v r|d   }d}nd|v rd|v r|d   |d   f}nt        d      t        ||||      }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.
        Tr5   Fr7   r8   zASize must contain either 'shortest_edge' or 'height' and 'width'.)r*   r6   rD   )r*   r+   rC   rD   )r    r   r   )	r>   rB   r*   r+   rC   rD   r?   r6   output_sizes	            r$   r   zChameleonImageProcessor.resize   s    2 !d"(D %'T/NDM2D`aa2//	
 
#/
 
 	
rA   r!   return_tensorsc                 >   ||n| j                   }||n| j                  }t        |dd      }||n| j                  }||n| j                  }||n| j
                  }t        |dd      }||n| j                  }||n| j                  }|	|	n| j                  }	|
|
n| j                  }
||n| j                  }||n| j                  }t        |      }t        |      st        d      t        |||	|
||||||
       |r|D cg c]  }| j!                  |       }}|D cg c]  }t#        |       }}t%        |d         r|rt&        j)                  d	       |t+        |d         }g }|D ]m  }|r| j-                  ||||
      }|r| j/                  |||      }|r| j1                  |||      }|	r| j3                  ||
||      }|j5                  |       o |D cg c]  }t7        |||       }}d|i}t9        ||      S c c}w c c}w c c}w )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.
        r*   F)r9   r6   r-   TzkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.)
r.   r/   r0   r1   r2   r,   r-   r)   r*   r+   r   zIt 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.)rB   r*   r+   rD   )rB   r*   rD   )rB   scalerD   )rB   meanstdrD   )input_channel_dimr(   )datatensor_type)r)   r*   r
   r+   r,   r-   r.   r/   r0   r1   r2   r3   r%   r   r    r   
blend_rgbar   r   loggerwarning_oncer   r   center_croprescale	normalizeappendr   r	   )r>   r!   r)   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   rG   rC   rD   rB   
all_imagesrM   s                      r$   
preprocessz"ChameleonImageProcessor.preprocess   s~   L "+!6IDNN	'tTYYTfN'38+9+E4K^K^!*!6IDNN	!)W[\	#-#9Zt
+9+E4K^K^'3'?|TEVEV#-#9Zt
!*!6IDNN	+9+E4K^K^$V,F#: 
 	&!)%!)	
 :@Adooe,AFA 6<<E.'<<6!9%*s
 $ >vay I
 	%E%dXars((u9Xi(j5ZkljiSd '  e$	%$ $
 ({N_`
 

 '>BBK B =8
s   	H'H(Hc                 $   t        |t        j                  j                        s|S |j                  dk(  r|S t	        j
                  |j                  d            }|dddddf   dk  j                         s|j                  d      S |dddddf   dz  }d|ddddt        j                  f   z
  dz  |ddddt        j                  f   |ddddddf   z  z   }t        j                  j                  |j                  d      d      S )	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.
        RGBRGBANr      g     o@   uint8)r   PILImagemodenparrayconvertanynewaxis	fromarrayastype)r>   rB   img_rgbaalphaimg_rgbs        r$   rO   z"ChameleonImageProcessor.blend_rgbaS  s     %1LZZ5 L88EMM&12 Aq!C',,.=='' Aq!E)uQ2::-..#5aBJJ>N8ORZ[\^_acbcac[cRd8ddyy""7>>'#:EBBrA   )__name__
__module____qualname____doc__model_input_namesr^   r_   LANCZOSboolr   strintr   r   floatr   r   r=   BICUBICra   ndarrayr   r   r   FIRSTr   r   rW   rO   __classcell__)r@   s   @r$   r'   r'   F   s   $L (( #'*yy'8'8#$(,2!:>9=#-- 38n- %	-
 - S>- - c5j)- - U5$u+#567- E%e"456- - 
-L (:'A'A>BDH/
zz/
 38n/
 %	/

 eC)9$9:;/
 $E#/?*?$@A/
 
/
b %& #'+# $!:>9=#;?2B2H2HDH!NCNC NC 38n	NC
 %NC NC NC NC NC NC U5$u+#567NC E%e"456NC NC !sJ!78NC ./NC  $E#/?*?$@A!NC" 
#NC 'NC`C
 Cz CrA   r'   )%rn   typingr   r   r   r   numpyra   image_processing_utilsr   r	   r
   image_transformsr   r   r   image_utilsr   r   r   r   r   r   r   r   r   utilsr   r   r   r   
get_loggerrk   rP   r^   r%   r'   r;   rA   r$   <module>r      s    + . .  U U 

 
 
 _ ^ 
		H	%D4Z(8#9 D.fC0 fCrA   