


import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

_lowercase       :      Dict	=	imread(R"digital_image_processing/image_data/lena_small.jpg")
_lowercase       :      List[str]	=	cvtColor(img, COLOR_BGR2GRAY)





def   _lowerCAmelCase				(   ) ->   Optional[Any]:





	"""simple docstring"""







	A								=				cn.convert_to_negative(UpperCamelCase__						)
	# assert negative_img array for at least one True
	assert negative_img.any()





def   _lowerCAmelCase				(   ) ->   List[Any]:





	"""simple docstring"""







	with Image.open("""digital_image_processing/image_data/lena_small.jpg"""						) as img:
		# Work around assertion for response
		assert str(cc.change_contrast(UpperCamelCase__							,					1_10						)						).startswith(
		    """<PIL.Image.Image image mode=RGB size=100x100 at"""						)





def   _lowerCAmelCase				(   ) ->   Optional[int]:





	"""simple docstring"""







	A								=				canny.gen_gaussian_kernel(9							,					sigma=1.4						)
	# Assert ambiguous array
	assert resp.all()





def   _lowerCAmelCase				(   ) ->   List[Any]:





	"""simple docstring"""







	A								=				imread("""digital_image_processing/image_data/lena_small.jpg"""							,					0						)
	# assert ambiguous array for all == True
	assert canny_img.all()
	A								=				canny.canny(UpperCamelCase__						)
	# assert canny array for at least one True
	assert canny_array.any()





def   _lowerCAmelCase				(   ) ->   Any:





	"""simple docstring"""







	assert gg.gaussian_filter(UpperCamelCase__							,					5							,					sigma=0.9						).all()





def   _lowerCAmelCase				(   ) ->   int:





	"""simple docstring"""







	A								=				array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]						)
	A								=				conv.img_convolve(UpperCamelCase__							,					UpperCamelCase__						).astype(UpperCamelCase__						)
	assert res.any()





def   _lowerCAmelCase				(   ) ->   List[Any]:





	"""simple docstring"""







	assert med.median_filter(UpperCamelCase__							,					3						).any()





def   _lowerCAmelCase				(   ) ->   List[str]:





	"""simple docstring"""







	A					,			A								=				sob.sobel_filter(UpperCamelCase__						)
	assert grad.any() and theta.any()





def   _lowerCAmelCase				(   ) ->   Union[str, Any]:





	"""simple docstring"""







	A								=				sp.make_sepia(UpperCamelCase__							,					20						)
	assert sepia.all()





def   _lowerCAmelCase				(   UpperCamelCase__:     str = "digital_image_processing/image_data/lena_small.jpg"						) ->   str:





	"""simple docstring"""







	A								=				bs.Burkes(imread(UpperCamelCase__							,					1						)							,					1_20						)
	burkes.process()
	assert burkes.output_img.any()





def   _lowerCAmelCase				(   UpperCamelCase__:     str = "digital_image_processing/image_data/lena_small.jpg"							,					) ->   List[str]:





	"""simple docstring"""







	A								=				rs.NearestNeighbour(imread(UpperCamelCase__							,					1						)							,					4_00							,					2_00						)
	nn.process()
	assert nn.output.any()





def   _lowerCAmelCase				(   ) ->   Union[str, Any]:





	"""simple docstring"""







	A								=				"""digital_image_processing/image_data/lena.jpg"""

	# Reading the image and converting it to grayscale.
	A								=				imread(UpperCamelCase__							,					0						)

	# Test for get_neighbors_pixel function() return not None
	A								=				0
	A								=				0
	A								=				image[x_coordinate][y_coordinate]

	A								=				lbp.get_neighbors_pixel(
	    UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__						)

	assert neighbors_pixels is not None

	# Test for local_binary_pattern function()
	# Create a numpy array as the same height and width of read image
	A								=				np.zeros((image.shape[0], image.shape[1])						)

	# Iterating through the image and calculating the local binary pattern value
	# for each pixel.
	for i in range(0							,					image.shape[0]						):
		for j in range(0							,					image.shape[1]						):
			A								=				lbp.local_binary_value(UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__						)

	assert lbp_image.any()







from __future__ import annotations

from typing import Any






class       _UpperCamelCase    :

				"""simple docstring"""







				def __init__(						self				,   a__				,   a__				,   a__ = 0   )	->				None:
					A					,			A								=				row, column
					A								=				[[default_value for c in range(a__   )] for r in range(a__   )]

				def __str__(						self   )	->				str:
					A								=				f'Matrix consist of {self.row} rows and {self.column} columns\n'

					# Make string identifier
					A								=				0
					for row_vector in self.array:
						for obj in row_vector:
							A								=				max(a__				,   len(str(a__   )   )   )
					A								=				f'%{max_element_length}s'

					# Make string and return
					def single_line(a__   ) -> str:
						nonlocal string_format_identifier
						A								=				"""["""
						line += ", ".join(string_format_identifier % (obj,) for obj in row_vector   )
						line += "]"
						return line

					s += "\n".join(single_line(a__   ) for row_vector in self.array   )
					return s

				def __repr__(						self   )	->				str:
					return str(self   )

				def      _UpperCAmelCase					(						self				,   a__   )	->				bool:
					if not (isinstance(a__				,   (list, tuple)   ) and len(a__   ) == 2):
						return False
					elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
						return False
					else:
						return True

				def __getitem__(						self				,   a__   )	->				Any:
					assert self.validate_indicies(a__   )
					return self.array[loc[0]][loc[1]]

				def __setitem__(						self				,   a__				,   a__   )	->				None:
					assert self.validate_indicies(a__   )
					A								=				value

				def __add__(						self				,   a__   )	->				Matrix:
					assert isinstance(a__				,   a__   )
					assert self.row == another.row and self.column == another.column

					# Add
					A								=				Matrix(self.row				,   self.column   )
					for r in range(self.row   ):
						for c in range(self.column   ):
							A								=				self[r, c] + another[r, c]
					return result

				def __neg__(						self   )	->				Matrix:
					A								=				Matrix(self.row				,   self.column   )
					for r in range(self.row   ):
						for c in range(self.column   ):
							A								=				-self[r, c]
					return result

				def __sub__(						self				,   a__   )	->				Matrix:
					return self + (-another)

				def __mul__(						self				,   a__   )	->				Matrix:

					if isinstance(a__				,   (int, float)   ):  # Scalar multiplication
						A								=				Matrix(self.row				,   self.column   )
						for r in range(self.row   ):
							for c in range(self.column   ):
								A								=				self[r, c] * another
						return result
					elif isinstance(a__				,   a__   ):  # Matrix multiplication
						assert self.column == another.row
						A								=				Matrix(self.row				,   another.column   )
						for r in range(self.row   ):
							for c in range(another.column   ):
								for i in range(self.column   ):
									result[r, c] += self[r, i] * another[i, c]
						return result
					else:
						A								=				f'Unsupported type given for another ({type(a__   )})'
						raise TypeError(a__   )

				def      _UpperCAmelCase					(						self   )	->				Matrix:
					A								=				Matrix(self.column				,   self.row   )
					for r in range(self.row   ):
						for c in range(self.column   ):
							A								=				self[r, c]
					return result

				def      _UpperCAmelCase					(						self				,   a__				,   a__   )	->				Any:
					assert isinstance(a__				,   a__   ) and isinstance(a__				,   a__   )
					assert self.row == self.column == u.row == v.row  # u, v should be column vector
					assert u.column == v.column == 1  # u, v should be column vector

					# Calculate
					A								=				v.transpose()
					A								=				(v_t * self * u)[0, 0] + 1
					if numerator_factor == 0:
						return None  # It's not invertable
					return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":





				def   _lowerCAmelCase				(   ) ->   None:





					"""simple docstring"""







					A								=				Matrix(3							,					3							,					0						)
					for i in range(3						):
						A								=				1
					print(f'a^(-1) is {ainv}'						)
					# u, v
					A								=				Matrix(3							,					1							,					0						)
					A					,			A					,			A								=				1, 2, -3
					A								=				Matrix(3							,					1							,					0						)
					A					,			A					,			A								=				4, -2, 5
					print(f'u is {u}'						)
					print(f'v is {v}'						)
					print(f'uv^T is {u * v.transpose()}'						)
					# Sherman Morrison
					print(f'(a + uv^T)^(-1) is {ainv.sherman_morrison(UpperCamelCase__							,					UpperCamelCase__						)}'						)





				def   _lowerCAmelCase				(   ) ->   None:





					"""simple docstring"""







					import doctest

					doctest.testmod()
				testa()



