






"""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

_lowerCAmelCase         =							imread(r"digital_image_processing/image_data/lena_small.jpg")
_lowerCAmelCase         =							cvtColor(img, COLOR_BGR2GRAY)






def 			__UpperCamelCase	(		):
	A_		:						Tuple	    =   cn.convert_to_negative(snake_case__					)
	# assert negative_img array for at least one True
	assert negative_img.any()






def 			__UpperCamelCase	(		):
	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 			__UpperCamelCase	(		):
	A_		:						Optional[Any]	    =   canny.gen_gaussian_kernel(9   ,   sigma=1.4					)
	# Assert ambiguous array
	assert resp.all()






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






def 			__UpperCamelCase	(		):
	assert gg.gaussian_filter(snake_case__   ,   5   ,   sigma=0.9					).all()






def 			__UpperCamelCase	(		):
	# laplace diagonals
	A_		:						Dict	    =   array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]					)
	A_		:						Union[str, Any]	    =   conv.img_convolve(snake_case__   ,   snake_case__					).astype(snake_case__					)
	assert res.any()






def 			__UpperCamelCase	(		):
	assert med.median_filter(snake_case__   ,   3					).any()






def 			__UpperCamelCase	(		):
	A_    ,     A_		:						Optional[int]	    =   sob.sobel_filter(snake_case__					)
	assert grad.any() and theta.any()






def 			__UpperCamelCase	(		):
	A_		:						Union[str, Any]	    =   sp.make_sepia(snake_case__   ,   20					)
	assert sepia.all()






def 			__UpperCamelCase	(		snake_case__ = "digital_image_processing/image_data/lena_small.jpg"					):
	A_		:						Tuple	    =   bs.Burkes(imread(snake_case__   ,   1					)   ,   120					)
	burkes.process()
	assert burkes.output_img.any()






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






def 			__UpperCamelCase	(		):
	A_		:						List[Any]	    =   """digital_image_processing/image_data/lena.jpg"""

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

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

	A_		:						Dict	    =   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
	A_		:						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]					):
			A_		:						Union[str, Any]	    =   lbp.local_binary_value(snake_case__   ,   snake_case__   ,   snake_case__					)

	assert lbp_image.any()









"""simple docstring"""
import unittest

import torch
from torch import nn

from diffusers.models.activations import get_activation



class      SCREAMING_SNAKE_CASE  (				unittest.TestCase						):





	"""simple docstring"""




	def    lowerCamelCase(self							):
		A_		:						Optional[int]	    =   get_activation("""swish"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.SiLU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						Dict	    =   get_activation("""silu"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.SiLU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						Optional[Any]	    =   get_activation("""mish"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.Mish							)

		self.assertEqual(act(torch.tensor(-200     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						int	    =   get_activation("""gelu"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.GELU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)

