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

from digital_image_processing.filters.convolve import img_convolve



def 			UpperCamelCase       (				lowerCAmelCase__						):
					'''simple docstring'''
					lowercase		      =		np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]						)
					lowercase		      =		np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]						)

					lowercase		      =		np.abs(img_convolve(__snake_case					,     __snake_case						)						)
					lowercase		      =		np.abs(img_convolve(__snake_case					,     __snake_case						)						)
					# modify the pix within [0, 255]
					lowercase		      =		dst_x * 255 / np.max(__snake_case						)
					lowercase		      =		dst_y * 255 / np.max(__snake_case						)

					lowercase		      =		np.sqrt((np.square(__snake_case						)) + (np.square(__snake_case						))						)
					lowercase		      =		dst_xy * 255 / np.max(__snake_case						)
					lowercase		      =		dst_xy.astype(np.uinta						)

					lowercase		      =		np.arctana(__snake_case					,     __snake_case						)
					return dst, theta


if __name__ == "__main__":
							# read original image
							lowercase__						:List[Any]					    =       imread("../image_data/lena.jpg")
							# turn image in gray scale value
							lowercase__						:Optional[Any]					    =       cvtColor(img, COLOR_BGR2GRAY)

							lowercase__    ,	lowercase__						:str					    =       sobel_filter(gray)

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









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


__lowerCamelCase								=      logging.get_logger(__name__)

__lowerCamelCase								=      {
    '''MCG-NJU/videomae-base''': '''https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json''',
}


class 	snake_case_			(lowercase__	):




       """simple docstring"""






       _lowerCamelCase           =					"""videomae"""



       def __init__(  self  ,lowercase=224  ,lowercase=16  ,lowercase=3  ,lowercase=16  ,lowercase=2  ,lowercase=768  ,lowercase=12  ,lowercase=12  ,lowercase=3072  ,lowercase="gelu"  ,lowercase=0.0  ,lowercase=0.0  ,lowercase=0.02  ,lowercase=1E-12  ,lowercase=True  ,lowercase=True  ,lowercase=6  ,lowercase=384  ,lowercase=4  ,lowercase=1536  ,lowercase=True  ,**lowercase  ,):

             """simple docstring"""





             super().__init__(**lowercase)

             UpperCAmelCase_	:						Optional[int]					   =		image_size
             UpperCAmelCase_	:						Optional[Any]					   =		patch_size
             UpperCAmelCase_	:						Tuple					   =		num_channels
             UpperCAmelCase_	:						Optional[int]					   =		num_frames
             UpperCAmelCase_	:						str					   =		tubelet_size

             UpperCAmelCase_	:						Any					   =		hidden_size
             UpperCAmelCase_	:						List[str]					   =		num_hidden_layers
             UpperCAmelCase_	:						List[str]					   =		num_attention_heads
             UpperCAmelCase_	:						Union[str, Any]					   =		intermediate_size
             UpperCAmelCase_	:						List[str]					   =		hidden_act
             UpperCAmelCase_	:						Tuple					   =		hidden_dropout_prob
             UpperCAmelCase_	:						Optional[Any]					   =		attention_probs_dropout_prob
             UpperCAmelCase_	:						Optional[Any]					   =		initializer_range
             UpperCAmelCase_	:						Dict					   =		layer_norm_eps
             UpperCAmelCase_	:						Tuple					   =		qkv_bias
             UpperCAmelCase_	:						int					   =		use_mean_pooling

             UpperCAmelCase_	:						List[Any]					   =		decoder_num_attention_heads
             UpperCAmelCase_	:						Optional[int]					   =		decoder_hidden_size
             UpperCAmelCase_	:						Any					   =		decoder_num_hidden_layers
             UpperCAmelCase_	:						Dict					   =		decoder_intermediate_size
             UpperCAmelCase_	:						str					   =		norm_pix_loss
