tfm.vision.augment.gaussian_filter2d

Performs Gaussian blur on image(s).

tfm.vision.augment.gaussian_filter2d(
    image: tf.Tensor,
    filter_shape: Union[List[int], Tuple[int, ...], int],
    sigma: Union[List[float], Tuple[float], float] = 1.0,
    padding: str = 'REFLECT',
    constant_values: Union[int, tf.Tensor] = 0,
    name: Optional[str] = None
) -> tf.Tensor

image Either a 2-D Tensor of shape [height, width], a 3-D Tensor of shape [height, width, channels], or a 4-D Tensor of shape [batch_size, height, width, channels].
filter_shape An integer or tuple/list of 2 integers, specifying the height and width of the 2-D gaussian filter. Can be a single integer to specify the same value for all spatial dimensions.
sigma A float or tuple/list of 2 floats, specifying the standard deviation in x and y direction the 2-D gaussian filter. Can be a single float to specify the same value for all spatial dimensions.
padding A string, one of "REFLECT", "CONSTANT", or "SYMMETRIC". The type of padding algorithm to use, which is compatible with mode argument in tf.pad. For more details, please refer to https://www.tensorflow.org/api_docs/python/tf/pad.
constant_values A scalar, the pad value to use in "CONSTANT" padding mode.
name A name for this operation (optional).

2-D, 3-D or 4-D Tensor of the same dtype as input.

ValueError If image is not 2, 3 or 4-dimensional, if padding is other than "REFLECT", "CONSTANT" or "SYMMETRIC", if filter_shape is invalid, or if sigma is invalid.