




'''simple docstring'''





from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros


def      UpperCamelCase_(	snake_case							:       Dict							,				snake_case							:       Dict     ):

							'''simple docstring'''






							snake_case_						=      k_size // 2
							snake_case_					,      snake_case_						=      mgrid[0 - center : k_size - center, 0 - center : k_size - center]
							snake_case_						=      1 / (2 * pi * sigma) * exp(-(square(snake_case     ) + square(snake_case     )) / (2 * square(snake_case     ))     )
							return g


def      UpperCamelCase_(	snake_case							:       List[str]							,				snake_case							:       Any							,				snake_case							:       List[Any]     ):

							'''simple docstring'''






							snake_case_					,      snake_case_						=      image.shape[0], image.shape[1]
							# dst image height and width
							snake_case_						=      height - k_size + 1
							snake_case_						=      width - k_size + 1

							# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
							snake_case_						=      zeros((dst_height * dst_width, k_size * k_size)     )
							snake_case_						=      0
							for i, j in product(range(snake_case     )							,				range(snake_case     )     ):
														snake_case_						=      ravel(image[i : i + k_size, j : j + k_size]     )
														snake_case_						=      window
														row += 1

							#  turn the kernel into shape(k*k, 1)
							snake_case_						=      gen_gaussian_kernel(snake_case							,				snake_case     )
							snake_case_						=      ravel(snake_case     )

							# reshape and get the dst image
							snake_case_						=      dot(snake_case							,				snake_case     ).reshape(snake_case							,				snake_case     ).astype(snake_case     )

							return dst


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

		# get values with two different mask size
		_SCREAMING_SNAKE_CASE							:   Optional[Any]      		= gaussian_filter(gray, 3, sigma=1)
		_SCREAMING_SNAKE_CASE							:   Any      		= gaussian_filter(gray, 5, sigma=0.8)

		# show result images
		imshow("gaussian filter with 3x3 mask", gaussianaxa)
		imshow("gaussian filter with 5x5 mask", gaussianaxa)
		waitKey()









'''simple docstring'''


from PIL import Image







def 				__lowerCamelCase				(   A__    ,						A__    )       ->	Image:






   """simple docstring"""

   def brightness(A__    ) -> float:
      return 128 + level + (c - 128)

   if not -255.0 <= level <= 255.0:
      raise ValueError('level must be between -255.0 (black) and 255.0 (white)'    )
   return img.point(A__    )


if __name__ == "__main__":
   # Load image
   with Image.open("image_data/lena.jpg") as img:
      # Change brightness to 100
      _lowerCamelCase	:       List[str]      	=	change_brightness(img, 100)
      brigt_img.save("image_data/lena_brightness.png", format="png")

