





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      A__       (    SCREAMING_SNAKE_CASE_   :      Any				,	SCREAMING_SNAKE_CASE_   :      int						)  ->  Any:






   """simple docstring"""







   _UpperCAmelCase           =   k_size // 2
   _UpperCAmelCase       ,      _UpperCAmelCase           =   mgrid[0 - center : k_size - center, 0 - center : k_size - center]
   _UpperCAmelCase           =   1 / (2 * pi * sigma) * exp(-(square(SCREAMING_SNAKE_CASE_						) + square(SCREAMING_SNAKE_CASE_						)) / (2 * square(SCREAMING_SNAKE_CASE_						))						)
   return g
def      A__       (    SCREAMING_SNAKE_CASE_   :      List[str]				,	SCREAMING_SNAKE_CASE_   :      int				,	SCREAMING_SNAKE_CASE_   :      Optional[Any]						)  ->  str:






   """simple docstring"""







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

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

   #  turn the kernel into shape(k*k, 1)
   _UpperCAmelCase           =   gen_gaussian_kernel(SCREAMING_SNAKE_CASE_				,	SCREAMING_SNAKE_CASE_						)
   _UpperCAmelCase           =   ravel(SCREAMING_SNAKE_CASE_						)

   # reshape and get the dst image
   _UpperCAmelCase           =   dot(SCREAMING_SNAKE_CASE_				,	SCREAMING_SNAKE_CASE_						).reshape(SCREAMING_SNAKE_CASE_				,	SCREAMING_SNAKE_CASE_						).astype(SCREAMING_SNAKE_CASE_						)

   return dst


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

   # get values with two different mask size
   UpperCAmelCase_           =	gaussian_filter(gray, 3, sigma=1)
   UpperCAmelCase_           =	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()






import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


UpperCAmelCase_           =	logging.get_logger(__name__)




class 			__UpperCamelCase    (							A__    ):





     def __init__(     self				,							*_UpperCamelCase				,							**_UpperCamelCase					):
        warnings.warn(
            '''The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
            ''' use GLPNImageProcessor instead.'''				,							_UpperCamelCase				,							)
        super().__init__(*_UpperCamelCase				,							**_UpperCamelCase					)