


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase						=		{
    '''configuration_x_clip''': [
        '''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XCLIPConfig''',
        '''XCLIPTextConfig''',
        '''XCLIPVisionConfig''',
    ],
    '''processing_x_clip''': ['''XCLIPProcessor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''XCLIPModel''',
		    '''XCLIPPreTrainedModel''',
		    '''XCLIPTextModel''',
		    '''XCLIPVisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_x_clip import (
		    XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    XCLIPConfig,
		    XCLIPTextConfig,
		    XCLIPVisionConfig,
		)
		from .processing_x_clip import XCLIPProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_x_clip import (
				    XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    XCLIPModel,
				    XCLIPPreTrainedModel,
				    XCLIPTextModel,
				    XCLIPVisionModel,
				)

else:
		import sys

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








from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		lowerCAmelCase__       :      List[Any]   					= k_size // 2
		lowerCAmelCase__					,     lowerCAmelCase__       :      Union[str, Any]   					= mgrid[0 - center : k_size - center, 0 - center : k_size - center]
		lowerCAmelCase__       :      str   					= 1 / (2 * pi * sigma) * exp(-(square(_a	) + square(_a	)) / (2 * square(_a	))	)
		return g






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a	):




		"""simple docstring"""






		lowerCAmelCase__					,     lowerCAmelCase__       :      int   					= image.shape[0], image.shape[1]
		# dst image height and width
		lowerCAmelCase__       :      Any   					= height - k_size + 1
		lowerCAmelCase__       :      Tuple   					= width - k_size + 1

		# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
		lowerCAmelCase__       :      int   					= zeros((dst_height * dst_width, k_size * k_size)	)
		lowerCAmelCase__       :      List[str]   					= 0
		for i, j in product(range(_a	)     ,       range(_a	)	):
				lowerCAmelCase__       :      Union[str, Any]   					= ravel(image[i : i + k_size, j : j + k_size]	)
				lowerCAmelCase__       :      List[Any]   					= window
				row += 1

		#  turn the kernel into shape(k*k, 1)
		lowerCAmelCase__       :      List[Any]   					= gen_gaussian_kernel(_a     ,       _a	)
		lowerCAmelCase__       :      str   					= ravel(_a	)

		# reshape and get the dst image
		lowerCAmelCase__       :      int   					= dot(_a     ,       _a	).reshape(_a     ,       _a	).astype(_a	)

		return dst


if __name__ == "__main__":
		# read original image
		lowerCamelCase						=		imread(R'''../image_data/lena.jpg''')
		# turn image in gray scale value
		lowerCamelCase						=		cvtColor(img, COLOR_BGR2GRAY)

		# get values with two different mask size
		lowerCamelCase						=		gaussian_filter(gray, 3, sigma=1)
		lowerCamelCase						=		gaussian_filter(gray, 5, sigma=0.8)

		# show result images
		imshow('''gaussian filter with 3x3 mask''', gaussianaxa)
		imshow('''gaussian filter with 5x5 mask''', gaussianaxa)
		waitKey()




