





__lowerCamelCase :  dict[str, float]										=  {
    "joule": 1.0,
    "kilojoule": 1000,
    "megajoule": 100_0000,
    "gigajoule": 10_0000_0000,
    "wattsecond": 1.0,
    "watthour": 3600,
    "kilowatthour": 360_0000,
    "newtonmeter": 1.0,
    "calorie_nutr": 4186.8,
    "kilocalorie_nutr": 418_6800.00,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4E-1_9,
    "britishthermalunit_it": 1055.0_5585,
    "footpound": 1.3_5_5_8_1_8,
}



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase							,     _lowerCAmelCase  )		->				float:
 if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
  UpperCamelCase			:      List[Any] 			=     (
      F"""Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
      F"""Valid values are: {", ".join(_lowerCAmelCase  )}"""
  )
  raise ValueError(_lowerCAmelCase  )
 return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
    import doctest

    doctest.testmod()







from PIL import Image



def 	A_       (  _lowerCAmelCase  )		->				Image:
 UpperCamelCase			,					UpperCamelCase			:      List[Any] 			=     image.size
 UpperCamelCase			:      Union[str, Any] 			=     0
 UpperCamelCase			:      List[str] 			=     image.load()
 for i in range(_lowerCAmelCase  ):
  for j in range(_lowerCAmelCase  ):
   UpperCamelCase			:      List[Any] 			=     pixels[j, i]
   mean += pixel
 mean //= width * height

 for j in range(_lowerCAmelCase  ):
  for i in range(_lowerCAmelCase  ):
   UpperCamelCase			:      Union[str, Any] 			=     255 if pixels[i, j] > mean else 0
 return image


if __name__ == "__main__":
    __lowerCamelCase :  Union[str, Any]										=  mean_threshold(Image.open("""path_to_image""").convert("""L"""))
    image.save("""output_image_path""")
