




"""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

SCREAMING_SNAKE_CASE    =	imread(r"digital_image_processing/image_data/lena_small.jpg")
SCREAMING_SNAKE_CASE    =	cvtColor(img, COLOR_BGR2GRAY)







def   _SCREAMING_SNAKE_CASE       (							)						->		List[str]:
 A__	=    cn.convert_to_negative(lowercase_						)
 # assert negative_img array for at least one True
 assert negative_img.any()







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







def   _SCREAMING_SNAKE_CASE       (							)						->		Dict:
 A__	=    canny.gen_gaussian_kernel(9      ,			sigma=1.4						)
 # Assert ambiguous array
 assert resp.all()







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







def   _SCREAMING_SNAKE_CASE       (							)						->		Dict:
 assert gg.gaussian_filter(lowercase_      ,			5      ,			sigma=0.9						).all()







def   _SCREAMING_SNAKE_CASE       (							)						->		Optional[Any]:
 # 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(lowercase_      ,			lowercase_						).astype(lowercase_						)
 assert res.any()







def   _SCREAMING_SNAKE_CASE       (							)						->		Any:
 assert med.median_filter(lowercase_      ,			3						).any()







def   _SCREAMING_SNAKE_CASE       (							)						->		int:
 A__,				A__	=    sob.sobel_filter(lowercase_						)
 assert grad.any() and theta.any()







def   _SCREAMING_SNAKE_CASE       (							)						->		Any:
 A__	=    sp.make_sepia(lowercase_      ,			20						)
 assert sepia.all()







def   _SCREAMING_SNAKE_CASE       (							lowercase_ = "digital_image_processing/image_data/lena_small.jpg"						)						->		str:
 A__	=    bs.Burkes(imread(lowercase_      ,			1						)      ,			1_20						)
 burkes.process()
 assert burkes.output_img.any()







def   _SCREAMING_SNAKE_CASE       (							lowercase_ = "digital_image_processing/image_data/lena_small.jpg"      ,			)						->		Tuple:
 A__	=    rs.NearestNeighbour(imread(lowercase_      ,			1						)      ,			4_00      ,			2_00						)
 nn.process()
 assert nn.output.any()







def   _SCREAMING_SNAKE_CASE       (							)						->		List[str]:
 A__	=    "digital_image_processing/image_data/lena.jpg"

 # Reading the image and converting it to grayscale.
 A__	=    imread(lowercase_      ,			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(
     lowercase_      ,			lowercase_      ,			lowercase_      ,			lowercase_						)

 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(lowercase_      ,			lowercase_      ,			lowercase_						)

 assert lbp_image.any()











"""simple docstring"""



import baseaa







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		bytes:
 return baseaa.aaaencode(string.encode("utf-8"						)						)







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
 return baseaa.aaadecode(lowercase_						).decode("utf-8"						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()





