

from pathlib import Path

import numpy as np
from PIL import Image

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    np.ndarray			):



     '''simple docstring'''





     lowercase__      , lowercase__      , lowercase__    :   int      =       rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
     return 0.2989 * r + 0.5870 * g + 0.1140 * b

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    np.ndarray			):



     '''simple docstring'''





     return (gray > 127) & (gray <= 255)

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    np.ndarray	,     SCREAMING_SNAKE_CASE_		:    np.ndarray			):



     '''simple docstring'''





     lowercase__    :   int      =       np.zeros_like(SCREAMING_SNAKE_CASE_			)
     lowercase__    :   str      =       np.zeros(
         (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)			)

     # Copy image to padded image
     lowercase__    :   Dict      =       image

     # Iterate over image & apply kernel
     for x in range(image.shape[1]			):
          for y in range(image.shape[0]			):
               lowercase__    :   str      =       (
                   kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
               ).sum()
               lowercase__    :   List[str]      =       int(summation > 0			)
     return output


if __name__ == "__main__":
       # read original image
       snake_case_			  = Path(__file__).resolve().parent / '''image_data''' / '''lena.jpg'''
       snake_case_			  = np.array(Image.open(lena_path))
       # kernel to be applied
       snake_case_			  = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
       snake_case_			  = dilation(gray_to_binary(rgb_to_gray(lena)), structuring_element)
       # Save the output image
       snake_case_			  = Image.fromarray(output).convert('''RGB''')
       pil_img.save('''result_dilation.png''')




import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


snake_case_			  = logging.get_logger(__name__)


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):





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

