import math
import os

import cva
import numpy as np

A_:      Optional[Any]        =			2_5_5.0


def 					__lowerCAmelCase			(  _A ,_A					):



							"""simple docstring"""


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

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


def 					__lowerCAmelCase			(  ):



							"""simple docstring"""


							_lowercase				=	os.path.dirname(os.path.realpath(_A					)					)
							# Loading images (original image and compressed image)
							_lowercase				=	cva.imread(os.path.join(_A ,"""image_data/original_image.png"""					)					)
							_lowercase				=	cva.imread(os.path.join(_A ,"""image_data/compressed_image.png"""					) ,1					)

							_lowercase				=	cva.imread(os.path.join(_A ,"""image_data/PSNR-example-base.png"""					)					)
							_lowercase				=	cva.imread(
							    os.path.join(_A ,"""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(_A ,_A					)} dB'''					)

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


if __name__ == "__main__":
				main()



import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A_:      Tuple        =			logging.get_logger(__name__)


class _lowercase					(       _UpperCAmelCase						):





							"""simple docstring"""




							def __init__(    self     ,   *UpperCAmelCase     ,   **UpperCAmelCase  ):







														'''simple docstring'''






														warnings.warn(
														    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
														    """ Please use MobileNetV2ImageProcessor instead."""     ,   UpperCAmelCase     ,   )
														super().__init__(*UpperCAmelCase     ,   **UpperCAmelCase  )


