
'''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 (       ):
						snake_case       :     str =    cn.convert_to_negative(A_       )
						# 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(A_    ,							110       )       ).startswith(
												    '''<PIL.Image.Image image mode=RGB size=100x100 at'''       )

def      A (       ):
						snake_case       :     Dict =    canny.gen_gaussian_kernel(9    ,							sigma=1.4       )
						# Assert ambiguous array
						assert resp.all()

def      A (       ):
						snake_case       :     List[str] =    imread('''digital_image_processing/image_data/lena_small.jpg'''    ,							0       )
						# assert ambiguous array for all == True
						assert canny_img.all()
						snake_case       :     Dict =    canny.canny(A_       )
						# assert canny array for at least one True
						assert canny_array.any()

def      A (       ):
						assert gg.gaussian_filter(A_    ,							5    ,							sigma=0.9       ).all()

def      A (       ):
						# laplace diagonals
						snake_case       :     Optional[Any] =    array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]       )
						snake_case       :     List[Any] =    conv.img_convolve(A_    ,							A_       ).astype(A_       )
						assert res.any()

def      A (       ):
						assert med.median_filter(A_    ,							3       ).any()

def      A (       ):
						snake_case,					snake_case       :     Tuple =    sob.sobel_filter(A_       )
						assert grad.any() and theta.any()

def      A (       ):
						snake_case       :     List[str] =    sp.make_sepia(A_    ,							20       )
						assert sepia.all()

def      A (       A_							:					str = "digital_image_processing/image_data/lena_small.jpg"       ):
						snake_case       :     Any =    bs.Burkes(imread(A_    ,							1       )    ,							120       )
						burkes.process()
						assert burkes.output_img.any()

def      A (       A_							:					str = "digital_image_processing/image_data/lena_small.jpg"    ,							):
						snake_case       :     Dict =    rs.NearestNeighbour(imread(A_    ,							1       )    ,							400    ,							200       )
						nn.process()
						assert nn.output.any()





def      A (       ):
						snake_case       :     List[Any] =    '''digital_image_processing/image_data/lena.jpg'''

						# Reading the image and converting it to grayscale.
						snake_case       :     List[Any] =    imread(A_    ,							0       )

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

						snake_case       :     Optional[int] =    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
						snake_case       :     List[Any] =    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]       ):
																		snake_case       :     int =    lbp.local_binary_value(A_    ,							A_    ,							A_       )

						assert lbp_image.any()



'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


UpperCAmelCase    					=   logging.get_logger(__name__)

class 						a   (				__magic_name__    ):




				def __init__(							self	:				Union[str, Any],    *SCREAMING_SNAKE_CASE_	:				Tuple,    **SCREAMING_SNAKE_CASE_	:				Tuple      ):
										warnings.warn(
										    '''The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
										    ''' Please use LayoutLMv2ImageProcessor instead.''',    SCREAMING_SNAKE_CASE_,    )
										super().__init__(*SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_      )

