


import copy

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging


__lowerCAmelCase									=				logging.get_logger(__name__)





class     __a     (       __UpperCamelCase ):
 __lowercase					:				Optional[Any]  	=					'hybrid-clip'
 __lowercase					:				Optional[int]  	=					True
 def __init__(  self							,					lowerCAmelCase__=512							,					**lowerCAmelCase__					)   ->							List[str]:




        '''simple docstring'''
        super().__init__(**lowerCAmelCase__					)

        if "text_config" not in kwargs:
               raise ValueError('`text_config` can not be `None`.'					)

        if "vision_config" not in kwargs:
               raise ValueError('`vision_config` can not be `None`.'					)

        lowercase__:  List[str]         =  kwargs.pop('text_config'					)
        lowercase__:  Union[str, Any]         =  kwargs.pop('vision_config'					)

        lowercase__:  str         =  text_config.pop('model_type'					)
        lowercase__:  List[str]         =  vision_config.pop('model_type'					)

        from transformers import AutoConfig

        lowercase__:  List[str]         =  AutoConfig.for_model(lowerCAmelCase__							,					**lowerCAmelCase__					)

        if vision_model_type == "clip":
               lowercase__:  Union[str, Any]         =  AutoConfig.for_model(lowerCAmelCase__							,					**lowerCAmelCase__					).vision_config
        elif vision_model_type == "clip_vision_model":
               from transformers import CLIPVisionConfig

               lowercase__:  List[str]         =  CLIPVisionConfig(**lowerCAmelCase__					)
        else:
               lowercase__:  Tuple         =  AutoConfig.for_model(lowerCAmelCase__							,					**lowerCAmelCase__					)

        lowercase__:  str         =  projection_dim
        lowercase__:  List[str]         =  1.0
 @classmethod
 def 						SCREAMING_SNAKE_CASE__  (  cls							,					lowerCAmelCase__							,					lowerCAmelCase__							,					**lowerCAmelCase__					)   ->							List[Any]:




        '''simple docstring'''
        return cls(text_config=text_config.to_dict()							,					vision_config=vision_config.to_dict()							,					**lowerCAmelCase__					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Any:




        '''simple docstring'''
        lowercase__:  int         =  copy.deepcopy(self.__dict__					)
        lowercase__:  str         =  self.text_config.to_dict()
        lowercase__:  List[Any]         =  self.vision_config.to_dict()
        lowercase__:  List[Any]         =  self.__class__.model_type
        return output






import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve




def   snake_case_	(    snake_case	)    ->							List[str]:
       lowercase__:  Any         =  np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]	)
       lowercase__:  Optional[Any]         =  np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]	)

       lowercase__:  Optional[int]         =  np.abs(img_convolve(snake_case     ,				snake_case	)	)
       lowercase__:  List[Any]         =  np.abs(img_convolve(snake_case     ,				snake_case	)	)
       # modify the pix within [0, 255]
       lowercase__:  Optional[Any]         =  dst_x * 2_55 / np.max(snake_case	)
       lowercase__:  Dict         =  dst_y * 2_55 / np.max(snake_case	)

       lowercase__:  Tuple         =  np.sqrt((np.square(snake_case	)) + (np.square(snake_case	))	)
       lowercase__:  str         =  dst_xy * 2_55 / np.max(snake_case	)
       lowercase__:  Tuple         =  dst_xy.astype(np.uinta	)

       lowercase__:  List[Any]         =  np.arctana(snake_case     ,				snake_case	)
       return dst, theta


if __name__ == "__main__":
 # read original image
 __lowerCAmelCase									=				imread('''../image_data/lena.jpg''')
 # turn image in gray scale value
 __lowerCAmelCase									=				cvtColor(img, COLOR_BGR2GRAY)

 __lowerCAmelCase			,__lowerCAmelCase									=				sobel_filter(gray)

 # show result images
 imshow('''sobel filter''', sobel_grad)
 imshow('''sobel theta''', sobel_theta)
 waitKey(0)


