





__magic_name__       					=      {
    0: 'underwear',
    1: 'pants',
    2: 'belt',
    3: 'suit',
    4: 'shoe',
    5: 'socks',
    6: 'shirt',
    7: 'tie',
    8: 'watch',
}

__magic_name__       					=      [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

__magic_name__       					=      [0 for x in range(len(graph))]
__magic_name__       					=      []







def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							Any      =       1
	while stack:
		lowerCamelCase_			:							str      =       stack.pop()
		print(lowercase_      ,					clothes[current_clothing])
		order += 1







def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							Any      =       1
	for v in graph[u]:
		if not visited[v]:
			depth_first_search(lowercase_      ,					lowercase_      ,					lowercase_)

	stack.append(lowercase_)







def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	for v in range(len(lowercase_)):
		if not visited[v]:
			depth_first_search(lowercase_      ,					lowercase_      ,					lowercase_)


if __name__ == "__main__":
							topological_sort(graph, visited)
							print(stack)
							print_stack(stack, clothes)





import math
import os

import cva
import numpy as np

__magic_name__       					=      2_55.0







def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							List[Any]      =       np.mean((original - contrast) ** 2)
	if mse == 0:
		return 100

	return 20 * math.logaa(PIXEL_MAX / math.sqrt(lowerCAmelCase_))







def     __magic_name__  (      ):
	'''simple docstring'''


	lowerCamelCase_			:							List[str]      =       os.path.dirname(os.path.realpath(lowerCAmelCase_))
	# Loading images (original image and compressed image)
	lowerCamelCase_			:							Optional[int]      =       cva.imread(os.path.join(lowerCAmelCase_      ,					"image_data/original_image.png"))
	lowerCamelCase_			:							List[str]      =       cva.imread(os.path.join(lowerCAmelCase_      ,					"image_data/compressed_image.png")      ,					1)

	lowerCamelCase_			:							str      =       cva.imread(os.path.join(lowerCAmelCase_      ,					"image_data/PSNR-example-base.png"))
	lowerCamelCase_			:							int      =       cva.imread(
	    os.path.join(lowerCAmelCase_      ,					"image_data/PSNR-example-comp-10.jpg")      ,					1)

	# Value expected: 29.73dB
	print("-- First Test --")
	print(F"""PSNR value is {peak_signal_to_noise_ratio(lowerCAmelCase_      ,					lowerCAmelCase_)} dB""")

	# # Value expected: 31.53dB (Wikipedia Example)
	print("\n-- Second Test --")
	print(F"""PSNR value is {peak_signal_to_noise_ratio(lowerCAmelCase_      ,					lowerCAmelCase_)} dB""")


if __name__ == "__main__":
							main()

