

"""simple docstring"""



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    {'configuration_vilt': ['VILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViltConfig']}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_       :						Optional[int]					=    ['ViltFeatureExtractor']
 SCREAMING_SNAKE_CASE_       :						Optional[Any]					=    ['ViltImageProcessor']
 SCREAMING_SNAKE_CASE_       :						Dict					=    ['ViltProcessor']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_       :						List[str]					=    [
     'VILT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'ViltForImageAndTextRetrieval',
     'ViltForImagesAndTextClassification',
     'ViltForTokenClassification',
     'ViltForMaskedLM',
     'ViltForQuestionAnswering',
     'ViltLayer',
     'ViltModel',
     'ViltPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_vilt import ViltFeatureExtractor
  from .image_processing_vilt import ViltImageProcessor
  from .processing_vilt import ViltProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_vilt import (
      VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
      ViltForImageAndTextRetrieval,
      ViltForImagesAndTextClassification,
      ViltForMaskedLM,
      ViltForQuestionAnswering,
      ViltForTokenClassification,
      ViltLayer,
      ViltModel,
      ViltPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE_       :						str					=    _LazyModule(__name__, globals()['__file__'], _import_structure)









"""simple docstring"""



from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like





def 			_snake_case  (     UpperCAmelCase_	:       Optional[int]       , UpperCAmelCase_	:       List[Any]=3      ):
     A__				      =	int(mask / 2      )
     # copy image size
     A__				      =	zeros_like(UpperCAmelCase_      )
     for i in range(UpperCAmelCase_       , gray_img.shape[0] - bd      ):
          for j in range(UpperCAmelCase_       , gray_img.shape[1] - bd      ):
               # get mask according with mask
               A__				      =	ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]      )
               # calculate mask median
               A__				      =	sort(UpperCAmelCase_      )[inta(divide((multiply(UpperCAmelCase_       , UpperCAmelCase_      ))       , 2      ) + 1      )]
               A__				      =	median
     return median_img


if __name__ == "__main__":
 # read original image
 SCREAMING_SNAKE_CASE_       :						int					=    imread('../image_data/lena.jpg')
 # turn image in gray scale value
 SCREAMING_SNAKE_CASE_       :						str					=    cvtColor(img, COLOR_BGR2GRAY)

 # get values with two different mask size
 SCREAMING_SNAKE_CASE_       :						List[Any]					=    median_filter(gray, 3)
 SCREAMING_SNAKE_CASE_       :						str					=    median_filter(gray, 5)

 # show result images
 imshow('median filter with 3x3 mask', medianaxa)
 imshow('median filter with 5x5 mask', medianaxa)
 waitKey(0)






