


'''simple docstring'''


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




def      lowerCamelCase					(      lowerCamelCase  :      int							,						lowerCamelCase  :      int							,						lowerCamelCase  :      int							,						lowerCamelCase  :      int							,						lowerCamelCase  :      int							,						lowerCamelCase  :      int):

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

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

                  # degree to radiant
                  A_						:  Dict          =				theta / 180 * np.pi
                  A_						:  int          =				np.cos(_theta)
                  A_						:  List[Any]          =				np.sin(_theta)

                  # get kernel x
                  A_						:  Dict          =				cos_theta * px + sin_theta * py

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

                  # fill kernel
                  A_						:  List[Any]          =				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
     __magic_name__			=      imread('../image_data/lena.jpg')
     # turn image in gray scale value
     __magic_name__			=      cvtColor(img, COLOR_BGR2GRAY)

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


__magic_name__			=      {}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __magic_name__			=      ['NllbTokenizer']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __magic_name__			=      ['NllbTokenizerFast']


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

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_nllb_fast import NllbTokenizerFast

else:
     import sys

     __magic_name__			=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
