"""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

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

def  _A(		):
							A__       :     List[Any]								=			cn.convert_to_negative(UpperCamelCase_							)
							# assert negative_img array for at least one True
							assert negative_img.any()

def  _A(		):
							with Image.open("""digital_image_processing/image_data/lena_small.jpg"""							) as img:
														# Work around assertion for response
														assert str(cc.change_contrast(UpperCamelCase_			,  110							)							).startswith(
														    """<PIL.Image.Image image mode=RGB size=100x100 at"""							)

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

def  _A(		):
							A__       :     List[str]								=			imread("""digital_image_processing/image_data/lena_small.jpg"""			,  0							)
							# assert ambiguous array for all == True
							assert canny_img.all()
							A__       :     int								=			canny.canny(UpperCamelCase_							)
							# assert canny array for at least one True
							assert canny_array.any()

def  _A(		):
							assert gg.gaussian_filter(UpperCamelCase_			,  5			,  sigma=0.9							).all()

def  _A(		):
							# laplace diagonals
							A__       :     Union[str, Any]								=			array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]							)
							A__       :     Optional[Any]								=			conv.img_convolve(UpperCamelCase_			,  UpperCamelCase_							).astype(UpperCamelCase_							)
							assert res.any()

def  _A(		):
							assert med.median_filter(UpperCamelCase_			,  3							).any()

def  _A(		):
							A__       :     Union[str, Any]								=			sob.sobel_filter(UpperCamelCase_							)
							assert grad.any() and theta.any()

def  _A(		):
							A__       :     Dict								=			sp.make_sepia(UpperCamelCase_			,  20							)
							assert sepia.all()

def  _A(		lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"							):
							A__       :     Union[str, Any]								=			bs.Burkes(imread(UpperCamelCase_			,  1							)			,  120							)
							burkes.process()
							assert burkes.output_img.any()

def  _A(		lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"			,  ):
							A__       :     Tuple								=			rs.NearestNeighbour(imread(UpperCamelCase_			,  1							)			,  400			,  200							)
							nn.process()
							assert nn.output.any()



def  _A(		):
							A__       :     List[str]								=			'''digital_image_processing/image_data/lena.jpg'''

							# Reading the image and converting it to grayscale.
							A__       :     int								=			imread(UpperCamelCase_			,  0							)

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

							A__       :     Optional[int]								=			lbp.get_neighbors_pixel(
							    UpperCamelCase_			,  UpperCamelCase_			,  UpperCamelCase_			,  UpperCamelCase_							)

							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__       :     Dict								=			lbp.local_binary_value(UpperCamelCase_			,  UpperCamelCase_			,  UpperCamelCase_							)

							assert lbp_image.any()









'''simple docstring'''





from ..utils import DummyObject, requires_backends




class 				UpperCAmelCase			(			metaclass=_snake_case						):
 UpperCAmelCase				=					["speech"]


 def __init__(      self							:	List[Any]			,       *__lowerCamelCase							:	List[Any]			,       **__lowerCamelCase							:	List[str] ):
    requires_backends(self			,       ['''speech'''] )




class 				UpperCAmelCase			(			metaclass=_snake_case						):
 UpperCAmelCase				=					["speech"]


 def __init__(      self							:	int			,       *__lowerCamelCase							:	List[Any]			,       **__lowerCamelCase							:	List[str] ):
    requires_backends(self			,       ['''speech'''] )



