



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





def 							A	(     _UpperCAmelCase				:   int							,   _UpperCAmelCase				:   int							,   _UpperCAmelCase				:   int							,   _UpperCAmelCase				:   int							,   _UpperCAmelCase				:   int							,   _UpperCAmelCase				:   int    )				-> np.ndarray:







			'''simple docstring'''



			if (ksize % 2) == 0:
						_UpperCAmelCase		       =   ksize + 1
			_UpperCAmelCase		       =   np.zeros((ksize, ksize)							,   dtype=np.floataa    )

			# each value
			for y in range(A__    ):
						for x in range(A__    ):
									# distance from center
									_UpperCAmelCase		       =   x - ksize // 2
									_UpperCAmelCase		       =   y - ksize // 2

									# degree to radiant
									_UpperCAmelCase		       =   theta / 180 * np.pi
									_UpperCAmelCase		       =   np.cos(_theta    )
									_UpperCAmelCase		       =   np.sin(_theta    )

									# get kernel x
									_UpperCAmelCase		       =   cos_theta * px + sin_theta * py

									# get kernel y
									_UpperCAmelCase		       =   -sin_theta * px + cos_theta * py

									# fill kernel
									_UpperCAmelCase		       =   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
							UpperCAmelCase__   =       imread("../image_data/lena.jpg")
							# turn image in gray scale value
							UpperCAmelCase__   =       cvtColor(img, COLOR_BGR2GRAY)

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

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

							waitKey(0)



from .imports import is_tqdm_available


if is_tqdm_available():
  from tqdm.auto import tqdm as _tqdm

from ..state import PartialState
def      a      (			A__	:   bool = True      ,   *A__	:   int      ,   **A__	:   Union[str, Any]     )    ->      List[str]:





      """simple docstring"""



      if not is_tqdm_available():
            raise ImportError('Accelerate\'s `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`.'     )
      _lowercase	       =False
      if main_process_only:
            _lowercase	       =PartialState().local_process_index == 0
      return _tqdm(*A__      ,   **A__      ,   disable=A__     )


