



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     (					)    ->			str:







   '''simple docstring'''
   _UpperCAmelCase			=       cn.convert_to_negative(_UpperCAmelCase   )
   # assert negative_img array for at least one True
   assert negative_img.any()





def 							A     (					)    ->			Union[str, 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							,       110   )   ).startswith(
          '<PIL.Image.Image image mode=RGB size=100x100 at'   )





def 							A     (					)    ->			Any:







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





def 							A     (					)    ->			Optional[Any]:







   '''simple docstring'''
   _UpperCAmelCase			=       imread('digital_image_processing/image_data/lena_small.jpg'							,       0   )
   # assert ambiguous array for all == True
   assert canny_img.all()
   _UpperCAmelCase			=       canny.canny(_UpperCAmelCase   )
   # assert canny array for at least one True
   assert canny_array.any()





def 							A     (					)    ->			Dict:







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





def 							A     (					)    ->			Dict:







   '''simple docstring'''
   _UpperCAmelCase			=       array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]   )
   _UpperCAmelCase			=       conv.img_convolve(_UpperCAmelCase							,       _UpperCAmelCase   ).astype(_UpperCAmelCase   )
   assert res.any()





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







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





def 							A     (					)    ->			int:







   '''simple docstring'''
   _UpperCAmelCase	,					_UpperCAmelCase			=       sob.sobel_filter(_UpperCAmelCase   )
   assert grad.any() and theta.any()





def 							A     (					)    ->			str:







   '''simple docstring'''
   _UpperCAmelCase			=       sp.make_sepia(_UpperCAmelCase							,       20   )
   assert sepia.all()





def 							A     (					_UpperCAmelCase    :       str = "digital_image_processing/image_data/lena_small.jpg"   )    ->			str:







   '''simple docstring'''
   _UpperCAmelCase			=       bs.Burkes(imread(_UpperCAmelCase							,       1   )							,       120   )
   burkes.process()
   assert burkes.output_img.any()





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







   '''simple docstring'''
   _UpperCAmelCase			=       rs.NearestNeighbour(imread(_UpperCAmelCase							,       1   )							,       400							,       200   )
   nn.process()
   assert nn.output.any()





def 							A     (					)    ->			Optional[Any]:







   '''simple docstring'''
   _UpperCAmelCase			=       'digital_image_processing/image_data/lena.jpg'

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

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

   _UpperCAmelCase			=       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
   _UpperCAmelCase			=       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]   ):
         _UpperCAmelCase			=       lbp.local_binary_value(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase   )

   assert lbp_image.any()





from __future__ import annotations

from itertools import permutations
from random import randint
from timeit import repeat





def 							A     (					)    ->			tuple[list[int], int]:







			'''simple docstring'''
			_UpperCAmelCase			=       [randint(-1_000							,       1_000   ) for i in range(10   )]
			_UpperCAmelCase			=       randint(-5_000							,       5_000   )
			return (arr, r)


UpperCAmelCase__       =	make_dataset()





def 							A     (					_UpperCAmelCase    :       list[int]							,       _UpperCAmelCase    :       int   )    ->			tuple[int, ...]:







			'''simple docstring'''
			for triplet in permutations(_UpperCAmelCase							,       3   ):
						if sum(_UpperCAmelCase   ) == target:
									return tuple(sorted(_UpperCAmelCase   )   )
			return (0, 0, 0)





def 							A     (					_UpperCAmelCase    :       list[int]							,       _UpperCAmelCase    :       int   )    ->			tuple[int, int, int]:







			'''simple docstring'''
			arr.sort()
			_UpperCAmelCase			=       len(_UpperCAmelCase   )
			for i in range(n - 1   ):
						_UpperCAmelCase	,					_UpperCAmelCase			=       i + 1, n - 1
						while left < right:
									if arr[i] + arr[left] + arr[right] == target:
												return (arr[i], arr[left], arr[right])
									elif arr[i] + arr[left] + arr[right] < target:
												left += 1
									elif arr[i] + arr[left] + arr[right] > target:
												right -= 1
			return (0, 0, 0)





def 							A     (					)    ->			tuple[float, float]:







			'''simple docstring'''
			_UpperCAmelCase			=       '\nfrom __main__ import dataset, triplet_sum1, triplet_sum2\n'
			_UpperCAmelCase			=       '\ntriplet_sum1(*dataset)\n'
			_UpperCAmelCase			=       '\ntriplet_sum2(*dataset)\n'
			_UpperCAmelCase			=       repeat(setup=_UpperCAmelCase							,       stmt=_UpperCAmelCase							,       repeat=5							,       number=10_000   )
			_UpperCAmelCase			=       repeat(setup=_UpperCAmelCase							,       stmt=_UpperCAmelCase							,       repeat=5							,       number=10_000   )
			return (min(_UpperCAmelCase   ), min(_UpperCAmelCase   ))


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

							testmod()
							UpperCAmelCase__       =	solution_times()
							print(f"""The time for naive implementation is {times[0]}.""")
							print(f"""The time for optimized implementation is {times[1]}.""")
