





'''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     :Optional[int]       =				imread(R'''digital_image_processing/image_data/lena_small.jpg''')
__SCREAMING_SNAKE_CASE     :Optional[int]       =				cvtColor(img, COLOR_BGR2GRAY)
def 	UpperCAmelCase_							(					)		->       int:


     '''simple docstring'''



     _UpperCAmelCase     							=   cn.convert_to_negative(__lowercase       )
     # assert negative_img array for at least one True
     assert negative_img.any()
def 	UpperCAmelCase_							(					)		->       Tuple:


     '''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(__lowercase			,     110       )       ).startswith(
              "<PIL.Image.Image image mode=RGB size=100x100 at"       )
def 	UpperCAmelCase_							(					)		->       Dict:


     '''simple docstring'''



     _UpperCAmelCase     							=   canny.gen_gaussian_kernel(9			,     sigma=1.4       )
     # Assert ambiguous array
     assert resp.all()
def 	UpperCAmelCase_							(					)		->       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(__lowercase       )
     # assert canny array for at least one True
     assert canny_array.any()
def 	UpperCAmelCase_							(					)		->       str:


     '''simple docstring'''



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


     '''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(__lowercase			,     __lowercase       ).astype(__lowercase       )
     assert res.any()
def 	UpperCAmelCase_							(					)		->       Union[str, Any]:


     '''simple docstring'''



     assert med.median_filter(__lowercase			,     3       ).any()
def 	UpperCAmelCase_							(					)		->       List[Any]:


     '''simple docstring'''



     _UpperCAmelCase							,  _UpperCAmelCase     							=   sob.sobel_filter(__lowercase       )
     assert grad.any() and theta.any()
def 	UpperCAmelCase_							(					)		->       Any:


     '''simple docstring'''



     _UpperCAmelCase     							=   sp.make_sepia(__lowercase			,     20       )
     assert sepia.all()
def 	UpperCAmelCase_							(					__lowercase							:      str = "digital_image_processing/image_data/lena_small.jpg"       )		->       List[str]:


     '''simple docstring'''



     _UpperCAmelCase     							=   bs.Burkes(imread(__lowercase			,     1       )			,     120       )
     burkes.process()
     assert burkes.output_img.any()
def 	UpperCAmelCase_							(					__lowercase							:      str = "digital_image_processing/image_data/lena_small.jpg"			,     )		->       Dict:


     '''simple docstring'''



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






def 	UpperCAmelCase_							(					)		->       str:


     '''simple docstring'''



     _UpperCAmelCase     							=   "digital_image_processing/image_data/lena.jpg"

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

     assert lbp_image.any()











'''simple docstring'''




import re

from filelock import FileLock


try:
  import nltk

  __SCREAMING_SNAKE_CASE     :Optional[int]       =				True
except (ImportError, ModuleNotFoundError):
  __SCREAMING_SNAKE_CASE     :str       =				False

if NLTK_AVAILABLE:
  with FileLock('''.lock''') as lock:
    nltk.download('''punkt''', quiet=True)
def 	UpperCAmelCase_							(					__lowercase							:      str       )		->       str:


     '''simple docstring'''



     re.sub("<n>"			,     ""			,     __lowercase       )  # remove pegasus newline char
     assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
     return "\n".join(nltk.sent_tokenize(__lowercase       )       )




