

import os

import pytest

from transformers.dynamic_module_utils import get_imports


__magic_name__            =  '''
import os
'''

__magic_name__            =  '''
def foo():
    import os
    return False
'''

__magic_name__            =  '''
def foo():
    def bar():
        if True:
            import os
        return False
    return bar()
'''

__magic_name__            =  '''
import os

try:
    import bar
except ImportError:
    raise ValueError()
'''

__magic_name__            =  '''
import os

def foo():
    try:
        import bar
    except ImportError:
        raise ValueError()
'''

__magic_name__            =  '''
import os

try:
    import bar
except (ImportError, AttributeError):
    raise ValueError()
'''

__magic_name__            =  '''
import os

try:
    import bar
except ImportError as e:
    raise ValueError()
'''

__magic_name__            =  '''
import os

try:
    import bar
except:
    raise ValueError()
'''

__magic_name__            =  '''
import os

try:
    import bar
    import baz
except ImportError:
    raise ValueError()
'''

__magic_name__            =  '''
import os

try:
    import bar
    import baz
except ImportError:
    x = 1
    raise ValueError()
'''

__magic_name__            =  [
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]





@pytest.mark.parametrize("case"    ,		__lowerCAmelCase							)
def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase							):
    snake_case__						=				os.path.join(__lowerCAmelCase    ,		"test_file.py"							)
    with open(__lowerCAmelCase    ,		"w"							) as _tmp_file:
        _tmp_file.write(__lowerCAmelCase							)

    snake_case__						=				get_imports(__lowerCAmelCase							)
    assert parsed_imports == ["os"]





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





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase    ,		__lowerCAmelCase    ,		__lowerCAmelCase    ,		__lowerCAmelCase    ,		__lowerCAmelCase							):

    # prepare kernel
    # the kernel size have to be odd
    if (ksize % 2) == 0:
        snake_case__						=				ksize + 1
    snake_case__						=				np.zeros((ksize, ksize)    ,		dtype=np.floataa							)

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

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

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

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

            # fill kernel
            snake_case__						=				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)



