





'''simple docstring'''

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






class    UpperCAmelCase	:
 def __init__(				self      :Tuple						,       lowercase_      :List[str]						,       lowercase_      :int						,       lowercase_      :int							)->							Tuple:
     if dst_width < 0 or dst_height < 0:
         raise ValueError("Destination width/height should be > 0"							)

     A__				=			img
     A__				=			img.shape[1]
     A__				=			img.shape[0]
     A__				=			dst_width
     A__				=			dst_height

     A__				=			self.src_w / self.dst_w
     A__				=			self.src_h / self.dst_h

     A__				=			A__				=			(
         np.ones((self.dst_h, self.dst_w, 3)						,       np.uinta							) * 2_55
     )
 def      UpperCAmelCase_							(				self      :Tuple							)->							Any:
     for i in range(self.dst_h							):
         for j in range(self.dst_w							):
             A__				=			self.img[self.get_y(lowercase_							)][self.get_x(lowercase_							)]
 def      UpperCAmelCase_							(				self      :Dict						,       lowercase_      :int							)->							int:
     return int(self.ratio_x * x							)



 def      UpperCAmelCase_							(				self      :Tuple						,       lowercase_      :int							)->							int:
     return int(self.ratio_y * y							)


if __name__ == "__main__":
  __lowerCAmelCase	,     __lowerCAmelCase							:	List[str]			=800, 600
  __lowerCAmelCase							:	List[Any]			=imread("image_data/lena.jpg", 1)
  __lowerCAmelCase							:	Union[str, 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'''

import warnings


warnings.warn(
    "memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
    "`from accelerate import find_executable_batch_size` to avoid this warning.",
    FutureWarning,
)



