
    sg_J                        d Z ddlmZmZmZmZ ddlZddlm	Z	 ddl
mZ ddlmZmZmZ ddlmZ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mZm Z  dd
l!m"Z"m#Z#  e	       rddl$Z$ e#jJ                  e&      Z'deee      fdZ( G d de      Z)y)z Image processor class for Vivit.    )DictListOptionalUnionN)is_vision_available)
TensorType   )BaseImageProcessorBatchFeatureget_size_dict)get_resize_output_image_sizerescaleresizeto_channel_dimension_format)IMAGENET_STANDARD_MEANIMAGENET_STANDARD_STDChannelDimension
ImageInputPILImageResamplinginfer_channel_dimension_formatis_scaled_imageis_valid_imageto_numpy_arrayvalid_imagesvalidate_preprocess_arguments)filter_out_non_signature_kwargsloggingreturnc                    t        | t        t        f      r,t        | d   t        t        f      rt        | d   d         r| S t        | t        t        f      rt        | d         r| gS t        |       r| ggS t	        d|        )Nr   z"Could not make batched video from )
isinstancelisttupler   
ValueError)videoss    c/var/www/html/venv/lib/python3.12/site-packages/transformers/models/vivit/image_processing_vivit.pymake_batchedr&   5   s    &4-(Zq	D%=-QVdeklmenopeqVr	FT5M	*~fQi/Hx		z
9&B
CC    c            #           e Zd ZdZdgZdde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deeeee   f      deeeee   f      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	 	 	 ddej"                  dee
ef   dedeee	ef      deee	ef      f
dZdddddddddddej*                  dfdededee	e
f   ded	ed
ee	e
f   dededededeeeee   f      deeeee   f      dee   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j*                  dfdededee	e
f   ded	ed
ee	e
f   dededededeeeee   f      deeeee   f      deee	ef      dedeee	ef      dej6                  j6                  f d       Z xZS )VivitImageProcessoraA  
    Constructs a Vivit 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[str, int]` *optional*, defaults to `{"shortest_edge": 256}`):
            Size of the output image after resizing. The shortest edge of the image will be resized to
            `size["shortest_edge"]` while maintaining the aspect ratio of the original image. Can be overriden 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 the `resample` parameter 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 the `do_center_crop`
            parameter in the `preprocess` method.
        crop_size (`Dict[str, int]`, *optional*, defaults to `{"height": 224, "width": 224}`):
            Size of the image after applying the center crop. Can be overridden by the `crop_size` parameter 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 the `do_rescale`
            parameter in the `preprocess` method.
        rescale_factor (`int` or `float`, *optional*, defaults to `1/127.5`):
            Defines the scale factor to use if rescaling the image. Can be overridden by the `rescale_factor` parameter
            in the `preprocess` method.
        offset (`bool`, *optional*, defaults to `True`):
            Whether to scale the image in both negative and positive directions. Can be overriden by the `offset` 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.
        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.
        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.
    pixel_valuesTNg?	do_resizesizeresampledo_center_crop	crop_size
do_rescalerescale_factoroffsetdo_normalize
image_mean	image_stdr   c                 @   t        |   d	i | ||nddi}t        |d      }||nddd}t        |d      }|| _        || _        || _        || _        || _        || _        || _	        || _
        |	| _        |
|
nt        | _        ||| _        y t        | _        y )
Nshortest_edge   Fdefault_to_square   )heightwidthr/   
param_name )super__init__r   r+   r,   r.   r/   r-   r0   r1   r2   r3   r   r4   r   r5   )selfr+   r,   r-   r.   r/   r0   r1   r2   r3   r4   r5   kwargs	__class__s                r%   rB   zVivitImageProcessor.__init__m   s     	"6"'tos-CTU;!*!6IsUX<Y	!)D	"	," $,((2(>*DZ&/&;AVr'   imagedata_formatinput_data_formatc                     t        |d      }d|v rt        ||d   d|      }n/d|v rd|v r|d   |d   f}nt        d|j                                t	        |f||||d|S )	a  
        Resize an image.

        Args:
            image (`np.ndarray`):
                Image to resize.
            size (`Dict[str, int]`):
                Size of the output image. If `size` is of the form `{"height": h, "width": w}`, the output image will
                have the size `(h, w)`. If `size` is of the form `{"shortest_edge": s}`, the output image will have its
                shortest edge of length `s` while keeping the aspect ratio of the original image.
            resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BILINEAR`):
                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 (`str` or `ChannelDimension`, *optional*):
                The channel dimension format of the input image. If not provided, it will be inferred.
        Fr9   r7   )r:   rH   r<   r=   zDSize must have 'height' and 'width' or 'shortest_edge' as keys. Got )r,   r-   rG   rH   )r   r   r#   keysr   )rC   rF   r,   r-   rG   rH   rD   output_sizes           r%   r   zVivitImageProcessor.resize   s    4 TU;d"6tO,YjK 'T/>4=9Kcdhdmdmdocpqrr
#/
 
 	
r'   scalec                 4    t        |f|||d|}|r|dz
  }|S )a  
        Rescale an image by a scale factor.

        If `offset` is `True`, the image has its values rescaled by `scale` and then offset by 1. If `scale` is
        1/127.5, the image is rescaled between [-1, 1].
            image = image * scale - 1

        If `offset` is `False`, and `scale` is 1/255, the image is rescaled between [0, 1].
            image = image * scale

        Args:
            image (`np.ndarray`):
                Image to rescale.
            scale (`int` or `float`):
                Scale to apply to the image.
            offset (`bool`, *optional*):
                Whether to scale the image in both negative and positive directions.
            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.
        )rL   rG   rH      )r   )rC   rF   rL   r2   rG   rH   rD   rescaled_images           r%   r   zVivitImageProcessor.rescale   s;    > !
KK\
`f
 +a/Nr'   c                    t        |||
|||||||
       |	r|st        d      t        |      }t        |      r|rt        j                  d       |t        |      }|r| j                  ||||      }|r| j                  |||      }|r| j                  |||	|      }|
r| j                  ||||      }t        |||      }|S )	zPreprocesses a single image.)
r0   r1   r3   r4   r5   r.   r/   r+   r,   r-   z0For offset, do_rescale must also be set to True.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.)rF   r,   r-   rH   )r,   rH   )rF   rL   r2   rH   )rF   meanstdrH   )input_channel_dim)r   r#   r   r   loggerwarning_oncer   r   center_cropr   	normalizer   )rC   rF   r+   r,   r-   r.   r/   r0   r1   r2   r3   r4   r5   rG   rH   s                  r%   _preprocess_imagez%VivitImageProcessor._preprocess_image   s    & 	&!)%!)	
 *OPP u%5!js
 $ >u EKKe$]nKoE$$UN_$`ELLuN6evLwENNZYbsNtE+E;Rcdr'   r$   return_tensorsc                    ||n| j                   }||n| j                  }||n| j                  }||n| j                  }||n| j                  }|	|	n| j
                  }	|
|
n| j                  }
||n| j                  }||n| j                  }||n| j                  }t        |d      }||n| j                  }t        |d      }t        |      st        d      t        |      }|D cg c]/  }|D cg c]!  }| j                  |||||||||	|
||||      # c}1 }}}d|i}t!        ||      S c c}w c c}}w )	a  
        Preprocess an image or batch of images.

        Args:
            videos (`ImageInput`):
                Video frames to preprocess. Expects a single or batch of video frames with pixel values ranging from 0
                to 255. If passing in frames 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 applying resize.
            resample (`PILImageResampling`, *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_centre_crop`):
                Whether to centre crop the image.
            crop_size (`Dict[str, int]`, *optional*, defaults to `self.crop_size`):
                Size of the image after applying the centre crop.
            do_rescale (`bool`, *optional*, defaults to `self.do_rescale`):
                Whether to rescale the image values between `[-1 - 1]` if `offset` is `True`, `[0, 1]` otherwise.
            rescale_factor (`float`, *optional*, defaults to `self.rescale_factor`):
                Rescale factor to rescale the image by if `do_rescale` is set to `True`.
            offset (`bool`, *optional*, defaults to `self.offset`):
                Whether to scale the image in both negative and positive directions.
            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.
            image_std (`float` or `List[float]`, *optional*, defaults to `self.image_std`):
                Image standard deviation.
            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:
                    - `ChannelDimension.FIRST`: image in (num_channels, height, width) format.
                    - `ChannelDimension.LAST`: image in (height, width, num_channels) format.
                    - Unset: Use the inferred 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.
        Fr9   r/   r>   zkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.)rF   r+   r,   r-   r.   r/   r0   r1   r2   r3   r4   r5   rG   rH   r*   )datatensor_type)r+   r-   r.   r0   r1   r2   r3   r4   r5   r,   r   r/   r   r#   r&   rX   r   )rC   r$   r+   r,   r-   r.   r/   r0   r1   r2   r3   r4   r5   rY   rG   rH   videoimgr[   s                      r%   
preprocesszVivitImageProcessor.preprocess!  s   H "+!6IDNN	'38+9+E4K^K^#-#9Zt
+9+E4K^K^!-4;;'3'?|TEVEV#-#9Zt
!*!6IDNN	'tTYYTU;!*!6IDNN	!)D	F#: 
 f%,  )
(  !#" ! &&'%#1')#1!!-)' +&7 ' 
 
. '>BB/
s   1	D>:&D9 D>9D>)TNN)__name__
__module____qualname____doc__model_input_namesr   BILINEARboolr   strintr   floatr   r   rB   npndarrayr   r   r   FIRSTr   rX   r   r   PILImager_   __classcell__)rE   s   @r%   r)   r)   B   st   &P (( #'9'B'B#$(,5!:>9=WW 38nW %	W
 W S>W W c5j)W W W U5$u+#567W E%e"456W 
WJ (:'B'B>BDH*
zz*
 38n*
 %	*

 eC)9$9:;*
 $E#/?*?$@A*
 
*
b >BDH&zz& S%Z & 	&
 eC)9$9:;& $E#/?*?$@A&V #'+#$( $!:>9=2B2H2HDH<< < 38n	<
 %< < S>< < < < < U5$u+#567< E%e"456< ./< $E#/?*?$@A<  
!<| %& #'+#$( $!:>9=;?(8(>(>DH!rCrC rC 38n	rC
 %rC rC S>rC rC rC rC rC U5$u+#567rC E%e"456rC !sJ!78rC &rC  $E#/?*?$@A!rC" 
#rC 'rCr'   r)   )*rc   typingr   r   r   r   numpyrj   transformers.utilsr   transformers.utils.genericr   image_processing_utilsr
   r   r   image_transformsr   r   r   r   image_utilsr   r   r   r   r   r   r   r   r   r   r   utilsr   r   rm   
get_loggerr`   rT   r&   r)   r@   r'   r%   <module>ry      s    ' . .  2 1 U U     > 			H	%
DDj!12 
DRC, RCr'   