




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__       :      Union[str, Any]  =   imread(r'digital_image_processing/image_data/lena_small.jpg')
SCREAMING_SNAKE_CASE__       :      List[str]  =   cvtColor(img, COLOR_BGR2GRAY)

def      A      (      )	-> int:
       lowerCamelCase   :      List[Any]			 =					cn.convert_to_negative(_SCREAMING_SNAKE_CASE    )
       # assert negative_img array for at least one True
       assert negative_img.any()

def      A      (      )	-> Union[str, Any]:
       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 ,110    )    ).startswith(
                  "<PIL.Image.Image image mode=RGB size=100x100 at"    )

def      A      (      )	-> Tuple:
       lowerCamelCase   :      List[Any]			 =					canny.gen_gaussian_kernel(9 ,sigma=1.4    )
       # Assert ambiguous array
       assert resp.all()

def      A      (      )	-> Any:
       lowerCamelCase   :      Tuple			 =					imread("digital_image_processing/image_data/lena_small.jpg" ,0    )
       # assert ambiguous array for all == True
       assert canny_img.all()
       lowerCamelCase   :      str			 =					canny.canny(_SCREAMING_SNAKE_CASE    )
       # assert canny array for at least one True
       assert canny_array.any()

def      A      (      )	-> Tuple:
       assert gg.gaussian_filter(_SCREAMING_SNAKE_CASE ,5 ,sigma=0.9    ).all()

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

def      A      (      )	-> Any:
       assert med.median_filter(_SCREAMING_SNAKE_CASE ,3    ).any()

def      A      (      )	-> str:
       lowerCamelCase ,      lowerCamelCase   :      List[Any]			 =					sob.sobel_filter(_SCREAMING_SNAKE_CASE    )
       assert grad.any() and theta.any()

def      A      (      )	-> Union[str, Any]:
       lowerCamelCase   :      Tuple			 =					sp.make_sepia(_SCREAMING_SNAKE_CASE ,20    )
       assert sepia.all()

def      A      (      _SCREAMING_SNAKE_CASE = "digital_image_processing/image_data/lena_small.jpg"    )	-> List[Any]:
       lowerCamelCase   :      Any			 =					bs.Burkes(imread(_SCREAMING_SNAKE_CASE ,1    ) ,120    )
       burkes.process()
       assert burkes.output_img.any()

def      A      (      _SCREAMING_SNAKE_CASE = "digital_image_processing/image_data/lena_small.jpg" ,)	-> Optional[Any]:
       lowerCamelCase   :      List[str]			 =					rs.NearestNeighbour(imread(_SCREAMING_SNAKE_CASE ,1    ) ,400 ,200    )
       nn.process()
       assert nn.output.any()


def      A      (      )	-> List[Any]:
       lowerCamelCase   :      Any			 =					"digital_image_processing/image_data/lena.jpg"

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

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

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

       assert lbp_image.any()










'''simple docstring'''
import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script




@require_cpu
class 			lowerCamelCase_   (	unittest.TestCase      ):






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          debug_launcher(test_script.main )






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          debug_launcher(test_ops.main )
