


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

from digital_image_processing.filters.convolve import img_convolve



def       lowerCAmelCase			(		lowerCAmelCase_			)->			Tuple:
				lowerCAmelCase_			:   int     					=					np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]			)
				lowerCAmelCase_			:   int     					=					np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]			)

				lowerCAmelCase_			:   Any     					=					np.abs(img_convolve(lowerCAmelCase_			, lowerCAmelCase_			)			)
				lowerCAmelCase_			:   Optional[Any]     					=					np.abs(img_convolve(lowerCAmelCase_			, lowerCAmelCase_			)			)
				# modify the pix within [0, 255]
				lowerCAmelCase_			:   Tuple     					=					dst_x * 255 / np.max(lowerCAmelCase_			)
				lowerCAmelCase_			:   Optional[Any]     					=					dst_y * 255 / np.max(lowerCAmelCase_			)

				lowerCAmelCase_			:   Any     					=					np.sqrt((np.square(lowerCAmelCase_			)) + (np.square(lowerCAmelCase_			))			)
				lowerCAmelCase_			:   Optional[Any]     					=					dst_xy * 255 / np.max(lowerCAmelCase_			)
				lowerCAmelCase_			:   Tuple     					=					dst_xy.astype(np.uinta			)

				lowerCAmelCase_			:   Union[str, Any]     					=					np.arctana(lowerCAmelCase_			, lowerCAmelCase_			)
				return dst, theta


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

						_UpperCAmelCase  ,       _UpperCAmelCase      :	str  =sobel_filter(gray)

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


"""simple docstring"""
from collections import defaultdict







def       UpperCamelCase_					(     lowerCamelCase							:					str   )						->     dict:



       """simple docstring"""







       __magic_name__			:		defaultdict[str, int]        =     defaultdict(lowerCamelCase   )
       # Creating a dictionary containing count of each word
       for word in sentence.split():
              occurrence[word] += 1
       return occurrence


if __name__ == "__main__":
 for word, count in word_occurrence("""INPUT STRING""").items():
  print(F"""{word}: {count}""")
