
"""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 						_snake_case       (	)  ->				str:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				List[Any]:


			'''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(UpperCAmelCase_      ,     1_1_0		)		).startswith(
						    """<PIL.Image.Image image mode=RGB size=100x100 at"""		)






def 						_snake_case       (	)  ->				List[Any]:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				int:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				Optional[int]:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				List[str]:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				Union[str, Any]:


			'''simple docstring'''





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






def 						_snake_case       (	)  ->				Union[str, Any]:


			'''simple docstring'''





			lowerCAmelCase_    :Tuple			     =  sob.sobel_filter(UpperCAmelCase_		)
			assert grad.any() and theta.any()






def 						_snake_case       (	)  ->				List[str]:


			'''simple docstring'''





			lowerCAmelCase_    :str			     =  sp.make_sepia(UpperCAmelCase_      ,     2_0		)
			assert sepia.all()






def 						_snake_case       (	lowercase__		:  str = "digital_image_processing/image_data/lena_small.jpg"		)  ->				Dict:


			'''simple docstring'''





			lowerCAmelCase_    :Dict			     =  bs.Burkes(imread(UpperCAmelCase_      ,     1		)      ,     1_2_0		)
			burkes.process()
			assert burkes.output_img.any()






def 						_snake_case       (	lowercase__		:  str = "digital_image_processing/image_data/lena_small.jpg"      ,     )  ->				Any:


			'''simple docstring'''





			lowerCAmelCase_    :List[Any]			     =  rs.NearestNeighbour(imread(UpperCAmelCase_      ,     1		)      ,     4_0_0      ,     2_0_0		)
			nn.process()
			assert nn.output.any()






def 						_snake_case       (	)  ->				Union[str, Any]:


			'''simple docstring'''





			lowerCAmelCase_    :Optional[Any]			     =  'digital_image_processing/image_data/lena.jpg'

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

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

			lowerCAmelCase_    :List[Any]			     =  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
			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_    :Any			     =  lbp.local_binary_value(UpperCAmelCase_      ,     UpperCAmelCase_      ,     UpperCAmelCase_		)

			assert lbp_image.any()










'''simple docstring'''



import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey





class    UpperCAmelCase_  :





    """simple docstring"""






    def __init__(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)				->     int:
         if dst_width < 0 or dst_height < 0:
              raise ValueError('Destination width/height should be > 0'	)

         __lowerCamelCase   :	Dict								=		img
         __lowerCamelCase   :	Any								=		img.shape[1]
         __lowerCamelCase   :	Optional[int]								=		img.shape[0]
         __lowerCamelCase   :	Dict								=		dst_width
         __lowerCamelCase   :	str								=		dst_height

         __lowerCamelCase   :	Dict								=		self.src_w / self.dst_w
         __lowerCamelCase   :	List[Any]								=		self.src_h / self.dst_h

         __lowerCamelCase   :	Optional[int]								=		(
             np.ones((self.dst_h, self.dst_w, 3)			,     np.uinta	) * 2_55
         )







    def       lowercase_				(							self	)				->     List[Any]:
         for i in range(self.dst_h	):
              for j in range(self.dst_w	):
                   __lowerCamelCase   :	Union[str, Any]								=		self.img[self.get_y(SCREAMING_SNAKE_CASE_	)][self.get_x(SCREAMING_SNAKE_CASE_	)]







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     int:
         return int(self.ratio_x * x	)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     int:
         return int(self.ratio_y * y	)


if __name__ == "__main__":
      A__						,					A__		:					Optional[Any]												=  800, 600
      A__		:					List[str]												=  imread("""image_data/lena.jpg""", 1)
      A__		:					List[Any]												=  NearestNeighbour(im, dst_w, dst_h)
      n.process()

      imshow(
          f'''Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}''', n.output
      )
      waitKey(0)
      destroyAllWindows()






