




"""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

lowerCAmelCase							:    Dict  							=     imread(r"""digital_image_processing/image_data/lena_small.jpg""")
lowerCAmelCase							:    int  							=     cvtColor(img, COLOR_BGR2GRAY)



def 					a__				(       )		->      Optional[int]:
			lowerCamelCase       =      cn.convert_to_negative(snake_case__       )
			# assert negative_img array for at least one True
			assert negative_img.any()



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



def 					a__				(       )		->      str:
			lowerCamelCase       =      canny.gen_gaussian_kernel(9 ,				sigma=1.4       )
			# Assert ambiguous array
			assert resp.all()



def 					a__				(       )		->      Tuple:
			lowerCamelCase       =      imread("""digital_image_processing/image_data/lena_small.jpg""" ,				0       )
			# assert ambiguous array for all == True
			assert canny_img.all()
			lowerCamelCase       =      canny.canny(snake_case__       )
			# assert canny array for at least one True
			assert canny_array.any()



def 					a__				(       )		->      Optional[int]:
			assert gg.gaussian_filter(snake_case__ ,				5 ,				sigma=0.9       ).all()



def 					a__				(       )		->      Union[str, Any]:
			# laplace diagonals
			lowerCamelCase       =      array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]       )
			lowerCamelCase       =      conv.img_convolve(snake_case__ ,				snake_case__       ).astype(snake_case__       )
			assert res.any()



def 					a__				(       )		->      int:
			assert med.median_filter(snake_case__ ,				3       ).any()



def 					a__				(       )		->      str:
			lowerCamelCase   ,     lowerCamelCase       =      sob.sobel_filter(snake_case__       )
			assert grad.any() and theta.any()



def 					a__				(       )		->      str:
			lowerCamelCase       =      sp.make_sepia(snake_case__ ,				20       )
			assert sepia.all()



def 					a__				(       snake_case__ = "digital_image_processing/image_data/lena_small.jpg"       )		->      Dict:
			lowerCamelCase       =      bs.Burkes(imread(snake_case__ ,				1       ) ,				1_20       )
			burkes.process()
			assert burkes.output_img.any()



def 					a__				(       snake_case__ = "digital_image_processing/image_data/lena_small.jpg" ,				)		->      List[str]:
			lowerCamelCase       =      rs.NearestNeighbour(imread(snake_case__ ,				1       ) ,				4_00 ,				2_00       )
			nn.process()
			assert nn.output.any()



def 					a__				(       )		->      Optional[Any]:
			lowerCamelCase       =      """digital_image_processing/image_data/lena.jpg"""

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

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

			lowerCamelCase       =      lbp.get_neighbors_pixel(
			    snake_case__ ,				snake_case__ ,				snake_case__ ,				snake_case__       )

			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
			lowerCamelCase       =      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]       ):
									lowerCamelCase       =      lbp.local_binary_value(snake_case__ ,				snake_case__ ,				snake_case__       )

			assert lbp_image.any()









"""simple docstring"""




from __future__ import annotations



def 					a__				(       snake_case__ ,				snake_case__ = None ,				snake_case__ = None       )		->      None:
			if start is None:
						lowerCamelCase       =      0

			if end is None:
						lowerCamelCase       =      len(snake_case__       ) - 1

			if start >= end:
						return

			lowerCamelCase       =      (start + end) // 2

			slowsort(snake_case__ ,				snake_case__ ,				snake_case__       )
			slowsort(snake_case__ ,				mid + 1 ,				snake_case__       )

			if sequence[end] < sequence[mid]:
						lowerCamelCase   ,     lowerCamelCase       =      sequence[mid], sequence[end]

			slowsort(snake_case__ ,				snake_case__ ,				end - 1       )


if __name__ == "__main__":
					from doctest import testmod

					testmod()



