





import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


UpperCAmelCase_   				=  logging.get_logger(__name__)
class       UpperCamelCase_		(	snake_case_       ):




					def __init__(		self					,    *lowerCAmelCase_					,    **lowerCAmelCase_	)		->				List[str]:
										warnings.warn(
										    'The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
										    ' Please use ConvNextImageProcessor instead.'					,    SCREAMING_SNAKE_CASE_					,    )
										super().__init__(*SCREAMING_SNAKE_CASE_					,    **SCREAMING_SNAKE_CASE_	)









"""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()


