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

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





def  _lowerCamelCase					(   ):
			lowerCamelCase						:int						  =     cn.convert_to_negative(a_)
			# assert negative_img array for at least one True
			assert negative_img.any()





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





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





def  _lowerCamelCase					(   ):
			lowerCamelCase						:str						  =     imread('''digital_image_processing/image_data/lena_small.jpg'''						,			0)
			# assert ambiguous array for all == True
			assert canny_img.all()
			lowerCamelCase						:Optional[Any]						  =     canny.canny(a_)
			# assert canny array for at least one True
			assert canny_array.any()





def  _lowerCamelCase					(   ):
			assert gg.gaussian_filter(a_						,			5						,			sigma=0.9).all()





def  _lowerCamelCase					(   ):
			# laplace diagonals
			lowerCamelCase						:List[Any]						  =     array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]])
			lowerCamelCase						:List[Any]						  =     conv.img_convolve(a_						,			a_).astype(a_)
			assert res.any()





def  _lowerCamelCase					(   ):
			assert med.median_filter(a_						,			3).any()





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Union[str, Any]						  =     sob.sobel_filter(a_)
			assert grad.any() and theta.any()





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Dict						  =     sp.make_sepia(a_						,			20)
			assert sepia.all()





def  _lowerCamelCase					(   a_				: str = "digital_image_processing/image_data/lena_small.jpg"):
			lowerCamelCase						:Any						  =     bs.Burkes(imread(a_						,			1)						,			1_20)
			burkes.process()
			assert burkes.output_img.any()





def  _lowerCamelCase					(   a_				: str = "digital_image_processing/image_data/lena_small.jpg"						,			):
			lowerCamelCase						:Tuple						  =     rs.NearestNeighbour(imread(a_						,			1)						,			4_00						,			2_00)
			nn.process()
			assert nn.output.any()





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Tuple						  =     '''digital_image_processing/image_data/lena.jpg'''

			# Reading the image and converting it to grayscale.
			lowerCamelCase						:Tuple						  =     imread(a_						,			0)

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

			lowerCamelCase						:Any						  =     lbp.get_neighbors_pixel(
			    a_						,			a_						,			a_						,			a_)

			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
			lowerCamelCase						: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]):
									lowerCamelCase						:Optional[int]						  =     lbp.local_binary_value(a_						,			a_						,			a_)

			assert lbp_image.any()




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

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





def  _lowerCamelCase					(   ):
			lowerCamelCase						:int						  =     cn.convert_to_negative(a_)
			# assert negative_img array for at least one True
			assert negative_img.any()





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





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





def  _lowerCamelCase					(   ):
			lowerCamelCase						:str						  =     imread('''digital_image_processing/image_data/lena_small.jpg'''						,			0)
			# assert ambiguous array for all == True
			assert canny_img.all()
			lowerCamelCase						:Optional[Any]						  =     canny.canny(a_)
			# assert canny array for at least one True
			assert canny_array.any()





def  _lowerCamelCase					(   ):
			assert gg.gaussian_filter(a_						,			5						,			sigma=0.9).all()





def  _lowerCamelCase					(   ):
			# laplace diagonals
			lowerCamelCase						:List[Any]						  =     array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]])
			lowerCamelCase						:List[Any]						  =     conv.img_convolve(a_						,			a_).astype(a_)
			assert res.any()





def  _lowerCamelCase					(   ):
			assert med.median_filter(a_						,			3).any()





def  _lowerCamelCase					(   ):
			lowerCamelCase  ,    lowerCamelCase						:Union[str, Any]						  =     sob.sobel_filter(a_)
			assert grad.any() and theta.any()





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Dict						  =     sp.make_sepia(a_						,			20)
			assert sepia.all()





def  _lowerCamelCase					(   a_				: str = "digital_image_processing/image_data/lena_small.jpg"):
			lowerCamelCase						:Any						  =     bs.Burkes(imread(a_						,			1)						,			1_20)
			burkes.process()
			assert burkes.output_img.any()





def  _lowerCamelCase					(   a_				: str = "digital_image_processing/image_data/lena_small.jpg"						,			):
			lowerCamelCase						:Tuple						  =     rs.NearestNeighbour(imread(a_						,			1)						,			4_00						,			2_00)
			nn.process()
			assert nn.output.any()





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Tuple						  =     '''digital_image_processing/image_data/lena.jpg'''

			# Reading the image and converting it to grayscale.
			lowerCamelCase						:Tuple						  =     imread(a_						,			0)

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

			lowerCamelCase						:Any						  =     lbp.get_neighbors_pixel(
			    a_						,			a_						,			a_						,			a_)

			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
			lowerCamelCase						: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]):
									lowerCamelCase						:Optional[int]						  =     lbp.local_binary_value(a_						,			a_						,			a_)

			assert lbp_image.any()



