


from pathlib import Path

import numpy as np
from PIL import Image


def 				lowerCamelCase__				(	A       :      np.ndarray					):




						'''simple docstring'''






						UpperCAmelCase    ,    UpperCAmelCase    ,    UpperCAmelCase					    =     rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
						return 0.2_989 * r + 0.5_870 * g + 0.1_140 * b


def 				lowerCamelCase__				(	A       :      np.ndarray					):




						'''simple docstring'''






						return (gray > 1_27) & (gray <= 2_55)


def 				lowerCamelCase__				(	A       :      np.ndarray				,       A       :      np.ndarray					):




						'''simple docstring'''






						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 > 0					)
						return output


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









'''simple docstring'''



# limitations under the License.

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from .pipelines import DiffusionPipeline, ImagePipelineOutput  # noqa: F401
from .utils import deprecate


deprecate(
    """pipelines_utils""",
    """0.22.0""",
    """Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.""",
    standard_warn=False,
    stacklevel=3,
)





