
'''simple docstring'''





from __future__ import annotations

from decimal import Decimal

from numpy import array



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(lowerCAmelCase__	) == 2 and len(matrix[0]	) == 2 and len(matrix[1]	) == 2:
										# Calculate the determinant of the matrix
										lowercase					=		float(
										    d(matrix[0][0]	) * d(matrix[1][1]	) - d(matrix[1][0]	) * d(matrix[0][1]	)	)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''	)

										# Creates a copy of the matrix with swapped positions of the elements
										lowercase					=		[[0.0, 0.0], [0.0, 0.0]]
										lowercase			,		lowercase					=		matrix[1][1], matrix[0][0]
										lowercase			,		lowercase					=		-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(lowerCAmelCase__	)	) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(lowerCAmelCase__	) == 3
					    and len(matrix[0]	) == 3
					    and len(matrix[1]	) == 3
					    and len(matrix[2]	) == 3
					):
										# Calculate the determinant of the matrix using Sarrus rule
										lowercase					=		float(
										    (
										        (d(matrix[0][0]	) * d(matrix[1][1]	) * d(matrix[2][2]	))
										        + (d(matrix[0][1]	) * d(matrix[1][2]	) * d(matrix[2][0]	))
										        + (d(matrix[0][2]	) * d(matrix[1][0]	) * d(matrix[2][1]	))
										    )
										    - (
										        (d(matrix[0][2]	) * d(matrix[1][1]	) * d(matrix[2][0]	))
										        + (d(matrix[0][1]	) * d(matrix[1][0]	) * d(matrix[2][2]	))
										        + (d(matrix[0][0]	) * d(matrix[1][2]	) * d(matrix[2][1]	))
										    )	)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''	)

										# Creating cofactor matrix
										lowercase					=		[
										    [d(0.0	), d(0.0	), d(0.0	)],
										    [d(0.0	), d(0.0	), d(0.0	)],
										    [d(0.0	), d(0.0	), d(0.0	)],
										]
										lowercase					=		(d(matrix[1][1]	) * d(matrix[2][2]	)) - (
										    d(matrix[1][2]	) * d(matrix[2][1]	)
										)
										lowercase					=		-(
										    (d(matrix[1][0]	) * d(matrix[2][2]	)) - (d(matrix[1][2]	) * d(matrix[2][0]	))
										)
										lowercase					=		(d(matrix[1][0]	) * d(matrix[2][1]	)) - (
										    d(matrix[1][1]	) * d(matrix[2][0]	)
										)
										lowercase					=		-(
										    (d(matrix[0][1]	) * d(matrix[2][2]	)) - (d(matrix[0][2]	) * d(matrix[2][1]	))
										)
										lowercase					=		(d(matrix[0][0]	) * d(matrix[2][2]	)) - (
										    d(matrix[0][2]	) * d(matrix[2][0]	)
										)
										lowercase					=		-(
										    (d(matrix[0][0]	) * d(matrix[2][1]	)) - (d(matrix[0][1]	) * d(matrix[2][0]	))
										)
										lowercase					=		(d(matrix[0][1]	) * d(matrix[1][2]	)) - (
										    d(matrix[0][2]	) * d(matrix[1][1]	)
										)
										lowercase					=		-(
										    (d(matrix[0][0]	) * d(matrix[1][2]	)) - (d(matrix[0][2]	) * d(matrix[1][0]	))
										)
										lowercase					=		(d(matrix[0][0]	) * d(matrix[1][1]	)) - (
										    d(matrix[0][1]	) * d(matrix[1][0]	)
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										lowercase					=		array(lowerCAmelCase__	)
										for i in range(3	):
															for j in range(3	):
																				lowercase					=		cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
										lowercase					=		array(lowerCAmelCase__	)
										for i in range(3	):
															for j in range(3	):
																				inverse_matrix[i][j] /= d(lowerCAmelCase__	)

        # Calculate the inverse of the matrix
										return [[float(d(lowerCAmelCase__	)	) or 0.0 for n in row] for row in inverse_matrix]
					raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''	)






from pathlib import Path

import numpy as np
from PIL import Image



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase			,		lowercase			,		lowercase					=		rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
					return 0.29_89 * r + 0.58_70 * g + 0.11_40 * b



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return (gray > 127) & (gray <= 255)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		np.zeros_like(lowerCAmelCase__	)
					lowercase					=		np.zeros(
					    (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)	)

					# Copy image to padded image
					lowercase					=		image

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


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




