





import numpy as np
from PIL import Image





def   _lowercase       (    _UpperCAmelCase					)    ->	np.array:
				lowerCamelCase			,	lowerCamelCase			,	lowerCamelCase									=rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
				return 0.2_9_8_9 * r + 0.5_8_7_0 * g + 0.1_1_4_0 * b





def   _lowercase       (    _UpperCAmelCase					)    ->	np.array:
				return (gray > 1_27) & (gray <= 2_55)





def   _lowercase       (    _UpperCAmelCase      ,   _UpperCAmelCase					)    ->	np.array:
				lowerCamelCase									=np.zeros_like(_UpperCAmelCase					)
				lowerCamelCase									=np.zeros(
				    (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)					)

				# Copy image to padded image
				lowerCamelCase									=image

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


# kernel to be applied
UpperCAmelCase__    :      Dict       					=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

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












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase__    :      Optional[Any]       					={
    '''configuration_rwkv''': ['''RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RwkvConfig''', '''RwkvOnnxConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Optional[Any]       					=[
							    '''RWKV_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''RwkvForCausalLM''',
							    '''RwkvModel''',
							    '''RwkvPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rwkv import (
														    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RwkvForCausalLM,
														    RwkvModel,
														    RwkvPreTrainedModel,
														)
else:
							import sys

							UpperCAmelCase__    :      int       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





