


'''simple docstring'''






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

__A	:	List[Any]     =     imread(r'digital_image_processing/image_data/lena_small.jpg')
__A	:	Optional[int]     =     cvtColor(img, COLOR_BGR2GRAY)





def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_		:							Dict			       =						cn.convert_to_negative(lowerCamelCase_ )
		# assert negative_img array for at least one True
		assert negative_img.any()





def      UpperCAmelCase      (		):







		'''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(lowerCamelCase_				,      1_10 ) ).startswith(
				    """<PIL.Image.Image image mode=RGB size=100x100 at""" )





def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_		:							Optional[Any]			       =						canny.gen_gaussian_kernel(9				,      sigma=1.4 )
		# Assert ambiguous array
		assert resp.all()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_		:							str			       =						imread("""digital_image_processing/image_data/lena_small.jpg"""				,      0 )
		# assert ambiguous array for all == True
		assert canny_img.all()
		snake_case_		:							Union[str, Any]			       =						canny.canny(lowerCamelCase_ )
		# assert canny array for at least one True
		assert canny_array.any()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		assert gg.gaussian_filter(lowerCamelCase_				,      5				,      sigma=0.9 ).all()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		# laplace diagonals
		snake_case_		:							Optional[Any]			       =						array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]] )
		snake_case_		:							Tuple			       =						conv.img_convolve(lowerCamelCase_				,      lowerCamelCase_ ).astype(lowerCamelCase_ )
		assert res.any()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		assert med.median_filter(lowerCamelCase_				,      3 ).any()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_       ,      snake_case_		:							Tuple			       =						sob.sobel_filter(lowerCamelCase_ )
		assert grad.any() and theta.any()





def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_		:							Dict			       =						sp.make_sepia(lowerCamelCase_				,      20 )
		assert sepia.all()





def      UpperCAmelCase      (		lowerCamelCase_  :str = "digital_image_processing/image_data/lena_small.jpg" ):







		'''simple docstring'''
		snake_case_		:							List[str]			       =						bs.Burkes(imread(lowerCamelCase_				,      1 )				,      1_20 )
		burkes.process()
		assert burkes.output_img.any()





def      UpperCAmelCase      (		lowerCamelCase_  :str = "digital_image_processing/image_data/lena_small.jpg"				,      ):







		'''simple docstring'''
		snake_case_		:							Union[str, Any]			       =						rs.NearestNeighbour(imread(lowerCamelCase_				,      1 )				,      4_00				,      2_00 )
		nn.process()
		assert nn.output.any()






def      UpperCAmelCase      (		):







		'''simple docstring'''
		snake_case_		:							List[str]			       =						"""digital_image_processing/image_data/lena.jpg"""

		# Reading the image and converting it to grayscale.
		snake_case_		:							Tuple			       =						imread(lowerCamelCase_				,      0 )

		# Test for get_neighbors_pixel function() return not None
		snake_case_		:							Tuple			       =						0
		snake_case_		:							Tuple			       =						0
		snake_case_		:							int			       =						image[x_coordinate][y_coordinate]

		snake_case_		:							Union[str, Any]			       =						lbp.get_neighbors_pixel(
		    lowerCamelCase_				,      lowerCamelCase_				,      lowerCamelCase_				,      lowerCamelCase_ )

		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
		snake_case_		:							List[Any]			       =						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] ):
						snake_case_		:							Optional[Any]			       =						lbp.local_binary_value(lowerCamelCase_				,      lowerCamelCase_				,      lowerCamelCase_ )

		assert lbp_image.any()



'''simple docstring'''






from __future__ import annotations





def      UpperCAmelCase      (		lowerCamelCase_  :int ):







		'''simple docstring'''
		snake_case_		:							List[str]			       =						[True] * limit
		snake_case_		:							Union[str, Any]			       =						False
		snake_case_		:							List[str]			       =						False
		snake_case_		:							Any			       =						True

		for i in range(3				,      int(limit**0.5 + 1 )				,      2 ):
				snake_case_		:							Tuple			       =						i * 2
				while index < limit:
						snake_case_		:							Any			       =						False
						snake_case_		:							Optional[Any]			       =						index + i

		snake_case_		:							List[str]			       =						[2]

		for i in range(3				,      lowerCamelCase_				,      2 ):
				if is_prime[i]:
						primes.append(lowerCamelCase_ )

		return primes





def      UpperCAmelCase      (		lowerCamelCase_  :int = 1_00_00_00 ):







		'''simple docstring'''
		snake_case_		:							Optional[int]			       =						prime_sieve(lowerCamelCase_ )
		snake_case_		:							Optional[Any]			       =						0
		snake_case_		:							Optional[int]			       =						0

		for i in range(len(lowerCamelCase_ ) ):
				for j in range(i + length				,      len(lowerCamelCase_ ) ):
						snake_case_		:							Optional[int]			       =						sum(primes[i:j] )
						if sol >= ceiling:
								break

						if sol in primes:
								snake_case_		:							Optional[Any]			       =						j - i
								snake_case_		:							Tuple			       =						sol

		return largest


if __name__ == "__main__":
							print(F'{solution() = }')