





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

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

def 							SCREAMING_SNAKE_CASE__       (  )      ->						List[str]:
  _lowercase							= cn.convert_to_negative(snake_case__     )
  # assert negative_img array for at least one True
  assert negative_img.any()

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

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Optional[int]:
  _lowercase							= canny.gen_gaussian_kernel(9			,							sigma=1.4     )
  # Assert ambiguous array
  assert resp.all()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Optional[Any]:
  _lowercase							= imread('digital_image_processing/image_data/lena_small.jpg'			,							0     )
  # assert ambiguous array for all == True
  assert canny_img.all()
  _lowercase							= canny.canny(snake_case__     )
  # assert canny array for at least one True
  assert canny_array.any()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Any:
  assert gg.gaussian_filter(snake_case__			,							5			,							sigma=0.9     ).all()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Tuple:
  # laplace diagonals
  _lowercase							= array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]     )
  _lowercase							= conv.img_convolve(snake_case__			,							snake_case__     ).astype(snake_case__     )
  assert res.any()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Tuple:
  assert med.median_filter(snake_case__			,							3     ).any()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Union[str, Any]:
  _lowercase						,		_lowercase							= sob.sobel_filter(snake_case__     )
  assert grad.any() and theta.any()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Union[str, Any]:
  _lowercase							= sp.make_sepia(snake_case__			,							20     )
  assert sepia.all()

def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :str = "digital_image_processing/image_data/lena_small.jpg"     )      ->						List[str]:
  _lowercase							= bs.Burkes(imread(snake_case__			,							1     )			,							120     )
  burkes.process()
  assert burkes.output_img.any()

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







def 							SCREAMING_SNAKE_CASE__       (  )      ->						int:
  _lowercase							= 'digital_image_processing/image_data/lena.jpg'

  # Reading the image and converting it to grayscale.
  _lowercase							= imread(snake_case__			,							0     )

  # Test for get_neighbors_pixel function() return not None
  _lowercase							= 0
  _lowercase							= 0
  _lowercase							= image[x_coordinate][y_coordinate]

  _lowercase							= lbp.get_neighbors_pixel(
      snake_case__			,							snake_case__			,							snake_case__			,							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
  _lowercase							= 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]     ):
      _lowercase							= lbp.local_binary_value(snake_case__			,							snake_case__			,							snake_case__     )

  assert lbp_image.any()






# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    """stable diffusion controlnet""",
    """0.22.0""",
    """Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.""",
    standard_warn=False,
    stacklevel=3,
)