'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__snake_case       :   Optional[int]  		=    logging.get_logger(__name__)

__snake_case       :   str  		=    {
    '''MBZUAI/swiftformer-xs''': '''https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json''',
}
class 							lowercase_    (     _A						):
				a_             =   """swiftformer"""







				def __init__(	self       ,     UpperCamelCase__=3       ,     UpperCamelCase__=[3, 3, 6, 4]       ,     UpperCamelCase__=[4_8, 5_6, 1_1_2, 2_2_0]       ,     UpperCamelCase__=4       ,     UpperCamelCase__=[True, True, True, True]       ,     UpperCamelCase__="gelu"       ,     UpperCamelCase__=3       ,     UpperCamelCase__=2       ,     UpperCamelCase__=1       ,     UpperCamelCase__=0.0       ,     UpperCamelCase__=True       ,     UpperCamelCase__=1e-5       ,     UpperCamelCase__=1e-5       ,     **UpperCamelCase__       ,     )				->       Dict:





					"""simple docstring"""

					super().__init__(**UpperCamelCase__				)
					UpperCAmelCase_				       =					num_channels
					UpperCAmelCase_				       =					depths
					UpperCAmelCase_				       =					embed_dims
					UpperCAmelCase_				       =					mlp_ratio
					UpperCAmelCase_				       =					downsamples
					UpperCAmelCase_				       =					hidden_act
					UpperCAmelCase_				       =					down_patch_size
					UpperCAmelCase_				       =					down_stride
					UpperCAmelCase_				       =					down_pad
					UpperCAmelCase_				       =					drop_path_rate
					UpperCAmelCase_				       =					use_layer_scale
					UpperCAmelCase_				       =					layer_scale_init_value
					UpperCAmelCase_				       =					batch_norm_eps


class 							lowercase_    (     _A						):
				a_             =   version.parse("""1.11"""						)







				@property
				def   lowerCamelCase_    (	self				)				->       Mapping[str, Mapping[int, str]]:





					"""simple docstring"""

					return OrderedDict(
					    [
					        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
					    ]				)







				@property
				def   lowerCamelCase_    (	self				)				->       float:





					"""simple docstring"""

					return 1e-4

'''simple docstring'''

import numpy as np
from PIL import Image



def lowerCamelCase__						(       A_       ):
 UpperCAmelCase_       ,       UpperCAmelCase_       ,       UpperCAmelCase_				       =					rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
 return 0.2989 * r + 0.5870 * g + 0.1140 * b



def lowerCamelCase__						(       A_       ):
 return (gray > 127) & (gray <= 255)



def lowerCamelCase__						(       A_       ,			A_       ):
 UpperCAmelCase_				       =					np.zeros_like(A_       )
 UpperCAmelCase_				       =					np.zeros(
     (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)       )

 # Copy image to padded image
 UpperCAmelCase_				       =					image

 # Iterate over image & apply kernel
 for x in range(image.shape[1]       ):
  for y in range(image.shape[0]       ):
   UpperCAmelCase_				       =					(
       kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
   ).sum()
   UpperCAmelCase_				       =					int(summation == 5       )
 return output


# kernel to be applied
__snake_case       :   List[str]  		=    np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

if __name__ == "__main__":
      # read original image
      __snake_case       :   int  		=    np.array(Image.open(R'''..\image_data\lena.jpg'''))
      # Apply erosion operation to a binary image
      __snake_case       :   str  		=    erosion(grayabinary(rgbagray(image)), structuring_element)
      # Save the output image
      __snake_case       :   List[Any]  		=    Image.fromarray(output).convert('''RGB''')
      pil_img.save('''result_erosion.png''')
