

'''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

__snake_case :	Union[str, Any]      						=			imread(r'digital_image_processing/image_data/lena_small.jpg')
__snake_case :	List[str]      						=			cvtColor(img, COLOR_BGR2GRAY)
def 						__lowerCamelCase       (   )       ->							int:






						"""simple docstring"""





						A__     :   List[Any]      =cn.convert_to_negative(_SCREAMING_SNAKE_CASE       )
						# assert negative_img array for at least one True
						assert negative_img.any()
def 						__lowerCamelCase       (   )       ->							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(_SCREAMING_SNAKE_CASE,		110       )       ).startswith(
												    """<PIL.Image.Image image mode=RGB size=100x100 at"""       )
def 						__lowerCamelCase       (   )       ->							Tuple:






						"""simple docstring"""





						A__     :   List[Any]      =canny.gen_gaussian_kernel(9,		sigma=1.4       )
						# Assert ambiguous array
						assert resp.all()
def 						__lowerCamelCase       (   )       ->							Any:






						"""simple docstring"""





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






						"""simple docstring"""





						assert gg.gaussian_filter(_SCREAMING_SNAKE_CASE,		5,		sigma=0.9       ).all()
def 						__lowerCamelCase       (   )       ->							List[Any]:






						"""simple docstring"""





						A__     :   Any      =array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]       )
						A__     :   Optional[int]      =conv.img_convolve(_SCREAMING_SNAKE_CASE,		_SCREAMING_SNAKE_CASE       ).astype(_SCREAMING_SNAKE_CASE       )
						assert res.any()
def 						__lowerCamelCase       (   )       ->							Any:






						"""simple docstring"""





						assert med.median_filter(_SCREAMING_SNAKE_CASE,		3       ).any()
def 						__lowerCamelCase       (   )       ->							str:






						"""simple docstring"""





						A__     :   List[Any]      =sob.sobel_filter(_SCREAMING_SNAKE_CASE       )
						assert grad.any() and theta.any()
def 						__lowerCamelCase       (   )       ->							Union[str, Any]:






						"""simple docstring"""





						A__     :   Tuple      =sp.make_sepia(_SCREAMING_SNAKE_CASE,		20       )
						assert sepia.all()
def 						__lowerCamelCase       (   __snake_case     :		List[str] = "digital_image_processing/image_data/lena_small.jpg"       )       ->							List[Any]:






						"""simple docstring"""





						A__     :   Any      =bs.Burkes(imread(_SCREAMING_SNAKE_CASE,		1       ),		120       )
						burkes.process()
						assert burkes.output_img.any()
def 						__lowerCamelCase       (   __snake_case     :		Optional[Any] = "digital_image_processing/image_data/lena_small.jpg",		)       ->							Optional[Any]:






						"""simple docstring"""





						A__     :   List[str]      =rs.NearestNeighbour(imread(_SCREAMING_SNAKE_CASE,		1       ),		400,		200       )
						nn.process()
						assert nn.output.any()
def 						__lowerCamelCase       (   )       ->							List[Any]:






						"""simple docstring"""





						A__     :   Any      ="digital_image_processing/image_data/lena.jpg"

						# Reading the image and converting it to grayscale.
						A__     :   List[Any]      =imread(_SCREAMING_SNAKE_CASE,		0       )

						# Test for get_neighbors_pixel function() return not None
						A__     :   Optional[int]      =0
						A__     :   Any      =0
						A__     :   List[Any]      =image[x_coordinate][y_coordinate]

						A__     :   str      =lbp.get_neighbors_pixel(
						    _SCREAMING_SNAKE_CASE,		_SCREAMING_SNAKE_CASE,		_SCREAMING_SNAKE_CASE,		_SCREAMING_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
						A__     :   Optional[int]      =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__     :   List[Any]      =lbp.local_binary_value(_SCREAMING_SNAKE_CASE,		_SCREAMING_SNAKE_CASE,		_SCREAMING_SNAKE_CASE       )

						assert lbp_image.any()







import random

def      A      (      _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )	-> tuple:
       lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase   :      Any			 =					[], [], []
       for element in data:
              if element < pivot:
                     less.append(_SCREAMING_SNAKE_CASE    )
              elif element > pivot:
                     greater.append(_SCREAMING_SNAKE_CASE    )
              else:
                     equal.append(_SCREAMING_SNAKE_CASE    )
       return less, equal, greater


def      A      (      _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )	-> str:
       # index = len(items) // 2 when trying to find the median
       #   (value of index when items is sorted)

       # invalid input
       if index >= len(_SCREAMING_SNAKE_CASE    ) or index < 0:
              return None

       lowerCamelCase   :      List[Any]			 =					items[random.randint(0 ,len(_SCREAMING_SNAKE_CASE    ) - 1    )]
       lowerCamelCase   :      Dict			 =					0
       lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase   :      Tuple			 =					_partition(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )
       lowerCamelCase   :      Union[str, Any]			 =					len(_SCREAMING_SNAKE_CASE    )
       lowerCamelCase   :      str			 =					len(_SCREAMING_SNAKE_CASE    )

       # index is the pivot
       if m <= index < m + count:
              return pivot
       # must be in smaller
       elif m > index:
              return quick_select(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )
       # must be in larger
       else:
              return quick_select(_SCREAMING_SNAKE_CASE ,index - (m + count)    )






