




'''simple docstring'''


import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey







class      SCREAMING_SNAKE_CASE    :






      def __init__( self   :  str						,						lowercase__   :  Any						,						lowercase__   :  int						,						lowercase__   :  int       ):


           '''simple docstring'''

           if dst_width < 0 or dst_height < 0:
                raise ValueError("""Destination width/height should be > 0"""       )

           a_     :							Tuple     						=  img
           a_     :							int     						=  img.shape[1]
           a_     :							List[str]     						=  img.shape[0]
           a_     :							Optional[int]     						=  dst_width
           a_     :							str     						=  dst_height

           a_     :							int     						=  self.src_w / self.dst_w
           a_     :							Dict     						=  self.src_h / self.dst_h

           a_     :							Tuple     						=  (
               np.ones((self.dst_h, self.dst_w, 3)						,						np.uinta       ) * 255
           )






      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           for i in range(self.dst_h       ):
                for j in range(self.dst_w       ):
                     a_     :							Optional[Any]     						=  self.img[self.get_y(lowercase__       )][self.get_x(lowercase__       )]






      def 							lowercase_						( self   :  Optional[Any]						,						lowercase__   :  int       ):


           '''simple docstring'''

           return int(self.ratio_x * x       )






      def 							lowercase_						( self   :  Optional[int]						,						lowercase__   :  int       ):


           '''simple docstring'''

           return int(self.ratio_y * y       )


if __name__ == "__main__":
 lowerCAmelCase_     ,   lowerCAmelCase_      :  Any				     =  800, 600
 lowerCAmelCase_      :  Dict				     =  imread('image_data/lena.jpg', 1)
 lowerCAmelCase_      :  Any				     =  NearestNeighbour(im, dst_w, dst_h)
 n.process()

 imshow(
     f"Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}", n.output
 )
 waitKey(0)
 destroyAllWindows()






'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCAmelCase_      :  Dict				     =  {
    'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  int				     =  [
     'GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'GraphormerForGraphClassification',
     'GraphormerModel',
     'GraphormerPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_graphormer import (
      GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      GraphormerForGraphClassification,
      GraphormerModel,
      GraphormerPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase_      :  Tuple				     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
