



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

UpperCAmelCase							 =					imread(R"""digital_image_processing/image_data/lena_small.jpg""")
UpperCAmelCase							 =					cvtColor(img, COLOR_BGR2GRAY)

def 			A_      (	):

				"""simple docstring"""
				a__				      =		cn.convert_to_negative(__a		)
				# assert negative_img array for at least one True
				assert negative_img.any()

def 			A_      (	):

				"""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(__a ,		110		)		).startswith(
								    """<PIL.Image.Image image mode=RGB size=100x100 at"""		)

def 			A_      (	):

				"""simple docstring"""
				a__				      =		canny.gen_gaussian_kernel(9 ,		sigma=1.4		)
				# Assert ambiguous array
				assert resp.all()

def 			A_      (	):

				"""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(__a		)
				# assert canny array for at least one True
				assert canny_array.any()

def 			A_      (	):

				"""simple docstring"""
				assert gg.gaussian_filter(__a ,		5 ,		sigma=0.9		).all()

def 			A_      (	):

				"""simple docstring"""
				# laplace diagonals
				a__				      =		array([[0.2_5, 0.5, 0.2_5], [0.5, -3, 0.5], [0.2_5, 0.5, 0.2_5]]		)
				a__				      =		conv.img_convolve(__a ,		__a		).astype(__a		)
				assert res.any()

def 			A_      (	):

				"""simple docstring"""
				assert med.median_filter(__a ,		3		).any()

def 			A_      (	):

				"""simple docstring"""
				a__      ,			a__				      =		sob.sobel_filter(__a		)
				assert grad.any() and theta.any()

def 			A_      (	):

				"""simple docstring"""
				a__				      =		sp.make_sepia(__a ,		20		)
				assert sepia.all()

def 			A_      (	__a     :				str = "digital_image_processing/image_data/lena_small.jpg"		):

				"""simple docstring"""
				a__				      =		bs.Burkes(imread(__a ,		1		) ,		120		)
				burkes.process()
				assert burkes.output_img.any()

def 			A_      (	__a     :				str = "digital_image_processing/image_data/lena_small.jpg" ,		):

				"""simple docstring"""
				a__				      =		rs.NearestNeighbour(imread(__a ,		1		) ,		400 ,		200		)
				nn.process()
				assert nn.output.any()




def 			A_      (	):

				"""simple docstring"""
				a__				      =		"""digital_image_processing/image_data/lena.jpg"""

				# Reading the image and converting it to grayscale.
				a__				      =		imread(__a ,		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(
				    __a ,		__a ,		__a ,		__a		)

				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(__a ,		__a ,		__a		)

				assert lbp_image.any()






def 			A_      (	__a     :				int ,		__a     :				int		):

				"""simple docstring"""
				return abs(__a		) if a == 0 else greatest_common_divisor(b % a ,		__a		)

def 			A_      (	__a     :				int ,		__a     :				int		):

				"""simple docstring"""
				while y:  # --> when y=0 then loop will terminate and return x as final GCD.
								a__      ,			a__				      =		y, x % y
				return abs(__a		)

def 			A_      (	):

				"""simple docstring"""
				try:
								a__				      =		input("""Enter two integers separated by comma (,): """		).split(""","""		)
								a__				      =		int(nums[0]		)
								a__				      =		int(nums[1]		)
								print(
								    F'''greatest_common_divisor({num_a}, {num_a}) = '''
								    F'''{greatest_common_divisor(__a ,		__a		)}'''		)
								print(F'''By iterative gcd({num_a}, {num_a}) = {gcd_by_iterative(__a ,		__a		)}'''		)
				except (IndexError, UnboundLocalError, ValueError):
								print("""Wrong input"""		)


if __name__ == "__main__":
	main()

