
    sg|@                        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mZmZ ddlmZmZmZm Z   e       rddl!Z! e jD                  e#      Z$d	eee      fd
Z% G d de	      Z&y)z#Image processor class for VideoMAE.    )DictListOptionalUnionN   )BaseImageProcessorBatchFeatureget_size_dict)get_resize_output_image_size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)
TensorTypefilter_out_non_signature_kwargsis_vision_available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    i/var/www/html/venv/lib/python3.12/site-packages/transformers/models/videomae/image_processing_videomae.pymake_batchedr%   2   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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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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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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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j4                  j4                  fd       Z xZS )VideoMAEImageProcessorao
  
    Constructs a VideoMAE 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": 224}`):
            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 `1/255`):
            Defines the scale factor to use if rescaling the image. 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.
        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p?	do_resizesizeresampledo_center_crop	crop_size
do_rescalerescale_factordo_normalize
image_mean	image_stdr   c                 2   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,   r/   r0   r1   r   r2   r   r3   )selfr*   r+   r,   r-   r.   r/   r0   r1   r2   r3   kwargs	__class__s               r$   r?   zVideoMAEImageProcessor.__init__g   s     	"6"'tos-CTU;!*!6IsUX<Y	!)D	"	," $,((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.
        Fr7   r5   )r8   rE   r9   r:   zDSize must have 'height' and 'width' or 'shortest_edge' as keys. Got )r+   r,   rD   rE   )r
   r   r"   keysr   )r@   rC   r+   r,   rD   rE   rA   output_sizes           r$   r   zVideoMAEImageProcessor.resize   s    4 TU;d"6tO,YjK 'T/>4=9Kcdhdmdmdocpqrr
#/
 
 	
r&   c                 t   t        |||	|
||||||
       t        |      }t        |      r|rt        j	                  d       |t        |      }|r| j                  ||||      }|r| j                  |||      }|r| j                  |||      }|	r| j                  ||
||      }t        |||      }|S )zPreprocesses a single image.)
r/   r0   r1   r2   r3   r-   r.   r*   r+   r,   zIt looks like you are trying to rescale already rescaled images. If the input images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again.)rC   r+   r,   rE   )r+   rE   )rC   scalerE   )rC   meanstdrE   )input_channel_dim)r   r   r   loggerwarning_oncer   r   center_croprescale	normalizer   )r@   rC   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   rD   rE   s                 r$   _preprocess_imagez(VideoMAEImageProcessor._preprocess_image   s    " 	&!)%!)	
 u%5!js
 $ >u EKKe$]nKoE$$UN_$`ELLuNVgLhENNZYbsNtE+E;Rcdr&   r#   return_tensorsc                 f   ||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}0 }}}d|i}t        ||      S c c}w c c}}w )	aH  
        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 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 [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.
            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.
        Fr7   r.   r;   zkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.)rC   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   rD   rE   r)   )datatensor_type)r*   r,   r-   r/   r0   r1   r2   r3   r+   r
   r.   r   r"   r%   rS   r	   )r@   r#   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   rT   rD   rE   videoimgrV   s                     r$   
preprocessz!VideoMAEImageProcessor.preprocess   sy   B "+!6IDNN	'38+9+E4K^K^#-#9Zt
+9+E4K^K^'3'?|TEVEV#-#9Zt
!*!6IDNN	'tTYYTU;!*!6IDNN	!)D	F#: 
 f%*  '
&  !!   &&'%#1')#1!-)' +&7 ' 
 
, '>BB-
s   !	D-*%D(D-(D-)__name__
__module____qualname____doc__model_input_namesr   BILINEARboolr   strintr   floatr   r   r?   npndarrayr   r   FIRSTr   rS   r   r   PILImagerZ   __classcell__)rB   s   @r$   r(   r(   ?   s   #J (( #'9'B'B#$(,3!:>9=WW 38nW %	W
 W S>W W c5j)W W U5$u+#567W E%e"456W 
WF (:'B'B>BDH*
zz*
 38n*
 %	*

 eC)9$9:;*
 $E#/?*?$@A*
 
*
^ #'+#$( $!:>9=2B2H2HDH77 7 38n	7
 %7 7 S>7 7 7 7 U5$u+#5677 E%e"4567 ./7 $E#/?*?$@A7 
7r %& #'+#$( $!:>9=;?(8(>(>DHmCmC mC 38n	mC
 %mC mC S>mC mC mC mC U5$u+#567mC E%e"456mC !sJ!78mC &mC $E#/?*?$@AmC  
!mC 'mCr&   r(   )'r^   typingr   r   r   r   numpyre   image_processing_utilsr   r	   r
   image_transformsr   r   r   image_utilsr   r   r   r   r   r   r   r   r   r   r   utilsr   r   r   r   rh   
get_loggerr[   rN   r%   r(   r=   r&   r$   <module>rr      s    * . .  U U 
    _ ^  
		H	%
DDj!12 
DZC/ ZCr&   