


"""simple docstring"""


import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey




def   snake_case		(     UpperCamelCase__       :						int			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						int    )   ->      np.ndarray:

      # prepare kernel
      # the kernel size have to be odd
      if (ksize % 2) == 0:
            lowerCamelCase					:					Tuple        =	ksize + 1
      lowerCamelCase					:					Optional[Any]        =	np.zeros((ksize, ksize)			,				dtype=np.floataa    )

      # each value
      for y in range(UpperCamelCase__    ):
            for x in range(UpperCamelCase__    ):
                  # distance from center
                  lowerCamelCase					:					int        =	x - ksize // 2
                  lowerCamelCase					:					Optional[Any]        =	y - ksize // 2

                  # degree to radiant
                  lowerCamelCase					:					Dict        =	theta / 180 * np.pi
                  lowerCamelCase					:					Dict        =	np.cos(_theta    )
                  lowerCamelCase					:					str        =	np.sin(_theta    )

                  # get kernel x
                  lowerCamelCase					:					List[str]        =	cos_theta * px + sin_theta * py

                  # get kernel y
                  lowerCamelCase					:					Tuple        =	-sin_theta * px + cos_theta * py

                  # fill kernel
                  lowerCamelCase					:					int        =	np.exp(
                      -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)    ) * np.cos(2 * np.pi * _x / lambd + psi    )

      return gabor


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    # read original image
    __lowerCamelCase      :int	    =		imread('../image_data/lena.jpg')
    # turn image in gray scale value
    __lowerCamelCase      :int	    =		cvtColor(img, COLOR_BGR2GRAY)

    # Apply multiple Kernel to detect edges
    __lowerCamelCase      :str	    =		np.zeros(gray.shape[:2])
    for theta in [0, 30, 60, 90, 120, 150]:
        __lowerCamelCase      :int	    =		gabor_filter_kernel(10, 8, theta, 10, 0, 0)
        out += filteraD(gray, CV_8UC3, kernel_aa)
    __lowerCamelCase      :int	    =		out / out.max() * 255
    __lowerCamelCase      :Tuple	    =		out.astype(np.uinta)

    imshow('Original', gray)
    imshow('Gabor filter with 20x20 mask and 6 directions', out)

    waitKey(0)








"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


__lowerCamelCase      :str	    =		{}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase      :Optional[Any]	    =		['GPTSw3Tokenizer']


if TYPE_CHECKING:
    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt_swa import GPTSwaTokenizer

else:
    import sys

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




