

from __future__ import annotations





def  _snake_case		(snake_case_					:     list[int | float]  )							->		int | float:
  if len(snake_case_  ) == 0:
    raise ValueError('find_max() arg is an empty sequence'  )
  __UpperCAmelCase	:  Any		=     nums[0]
  for x in nums:
    if x > max_num:
      __UpperCAmelCase	:  Optional[int]		=     x
  return max_num


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)











"""simple docstring"""





import math
import os

import cva
import numpy as np

_lowercase						   =     2_55.0

def 		lowerCAmelCase				(			lowerCamelCase   ,      lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       Tuple				      =       np.mean((original - contrast) ** 2		)
						if mse == 0:
												return 100

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

def 		lowerCAmelCase				(			):
						'''simple docstring'''


						snake_case__							:       Any				      =       os.path.dirname(os.path.realpath(lowerCamelCase		)		)
						# Loading images (original image and compressed image)
						snake_case__							:       Any				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/original_image.png'''		)		)
						snake_case__							:       Any				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/compressed_image.png'''		)   ,      1		)

						snake_case__							:       Optional[Any]				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/PSNR-example-base.png'''		)		)
						snake_case__							:       Tuple				      =       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()


