

'''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      					=     imread(R"""digital_image_processing/image_data/lena_small.jpg""")
_lowerCamelCase      					=     cvtColor(img, COLOR_BGR2GRAY)


def  a__       (    )     ->					Any:


	"""simple docstring"""





	UpperCAmelCase_     :      Optional[Any]						=  cn.convert_to_negative(_SCREAMING_SNAKE_CASE				)
	# assert negative_img array for at least one True
	assert negative_img.any()


def  a__       (    )     ->					Dict:


	"""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	,				1_10				)				).startswith(
		    "<PIL.Image.Image image mode=RGB size=100x100 at"				)


def  a__       (    )     ->					Optional[int]:


	"""simple docstring"""





	UpperCAmelCase_     :      Optional[Any]						=  canny.gen_gaussian_kernel(9	,				sigma=1.4				)
	# Assert ambiguous array
	assert resp.all()


def  a__       (    )     ->					str:


	"""simple docstring"""





	UpperCAmelCase_     :      Any						=  imread("digital_image_processing/image_data/lena_small.jpg"	,				0				)
	# assert ambiguous array for all == True
	assert canny_img.all()
	UpperCAmelCase_     :      Optional[int]						=  canny.canny(_SCREAMING_SNAKE_CASE				)
	# assert canny array for at least one True
	assert canny_array.any()


def  a__       (    )     ->					List[Any]:


	"""simple docstring"""





	assert gg.gaussian_filter(_SCREAMING_SNAKE_CASE	,				5	,				sigma=0.9				).all()


def  a__       (    )     ->					str:


	"""simple docstring"""





	UpperCAmelCase_     :      List[str]						=  array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]				)
	UpperCAmelCase_     :      Any						=  conv.img_convolve(_SCREAMING_SNAKE_CASE	,				_SCREAMING_SNAKE_CASE				).astype(_SCREAMING_SNAKE_CASE				)
	assert res.any()


def  a__       (    )     ->					Tuple:


	"""simple docstring"""





	assert med.median_filter(_SCREAMING_SNAKE_CASE	,				3				).any()


def  a__       (    )     ->					Dict:


	"""simple docstring"""





	UpperCAmelCase_					,					UpperCAmelCase_     :      Optional[Any]						=  sob.sobel_filter(_SCREAMING_SNAKE_CASE				)
	assert grad.any() and theta.any()


def  a__       (    )     ->					str:


	"""simple docstring"""





	UpperCAmelCase_     :      Union[str, Any]						=  sp.make_sepia(_SCREAMING_SNAKE_CASE	,				20				)
	assert sepia.all()


def  a__       (    _SCREAMING_SNAKE_CASE   :       str = "digital_image_processing/image_data/lena_small.jpg"				)     ->					Optional[int]:


	"""simple docstring"""





	UpperCAmelCase_     :      List[str]						=  bs.Burkes(imread(_SCREAMING_SNAKE_CASE	,				1				)	,				1_20				)
	burkes.process()
	assert burkes.output_img.any()


def  a__       (    _SCREAMING_SNAKE_CASE   :       str = "digital_image_processing/image_data/lena_small.jpg"	,				)     ->					Optional[int]:


	"""simple docstring"""





	UpperCAmelCase_     :      str						=  rs.NearestNeighbour(imread(_SCREAMING_SNAKE_CASE	,				1				)	,				4_00	,				2_00				)
	nn.process()
	assert nn.output.any()





def  a__       (    )     ->					str:


	"""simple docstring"""





	UpperCAmelCase_     :      List[Any]						=  "digital_image_processing/image_data/lena.jpg"

	# Reading the image and converting it to grayscale.
	UpperCAmelCase_     :      Optional[int]						=  imread(_SCREAMING_SNAKE_CASE	,				0				)

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

	UpperCAmelCase_     :      Optional[Any]						=  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
	UpperCAmelCase_     :      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]				):
			UpperCAmelCase_     :      List[str]						=  lbp.local_binary_value(_SCREAMING_SNAKE_CASE	,				_SCREAMING_SNAKE_CASE	,				_SCREAMING_SNAKE_CASE				)

	assert lbp_image.any()






"""simple docstring"""




from cva import destroyAllWindows, imread, imshow, waitKey




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase			,					_lowercase:      Union[str, Any]   			=  img.shape[0], img.shape[1]

  # converting each pixel's color to its negative
  for i in range(_UpperCamelCase    ):
    for j in range(_UpperCamelCase    ):
      _lowercase:      Dict   			=  [255, 255, 255] - img[i][j]

  return img


if __name__ == "__main__":
  # read original image
  A__ :       Optional[Any]				= imread('image_data/lena.jpg', 1)

  # convert to its negative
  A__ :       Dict				= convert_to_negative(img)

  # show result image
  imshow('negative of original image', img)
  waitKey(0)
  destroyAllWindows()
