

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowercase_									=    {"configuration_detr": ["DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetrConfig", "DetrOnnxConfig"]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase_									=    ["DetrFeatureExtractor"]
     lowercase_									=    ["DetrImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase_									=    [
         "DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
         "DetrForObjectDetection",
         "DetrForSegmentation",
         "DetrModel",
         "DetrPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_detr import DetrFeatureExtractor
          from .image_processing_detr import DetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_detr import (
              DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DetrForObjectDetection,
              DetrForSegmentation,
              DetrModel,
              DetrPreTrainedModel,
          )

else:
     import sys

     lowercase_									=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




import math
import os

import cva
import numpy as np

lowercase_									=    255.0
def 		_snake_case(       SCREAMING_SNAKE_CASE__     :      float       ,     SCREAMING_SNAKE_CASE__     :      float )				-> float:





    '''simple docstring'''






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

    return 20 * math.logaa(PIXEL_MAX / math.sqrt(SCREAMING_SNAKE_CASE__ ) )
def 		_snake_case(       )				-> None:





    '''simple docstring'''






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

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

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


if __name__ == "__main__":
     main()

