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tfa.image.mean_filter2d
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Perform mean filtering on image(s).
@tf.function
tfa.image.mean_filter2d(
image: tfa.types.TensorLike
,
filter_shape: Union[int, Iterable[int]] = (3, 3),
padding: str = 'REFLECT',
constant_values: tfa.types.TensorLike
= 0,
name: Optional[str] = None
) -> tf.Tensor
Used in the notebooks
Args |
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 mean filter. Can be a single integer
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).
|
Returns |
2-D, 3-D or 4-D Tensor of the same dtype as input.
|
Raises |
ValueError
|
If image is not 2, 3 or 4-dimensional,
if padding is other than "REFLECT", "CONSTANT" or "SYMMETRIC",
or if filter_shape is invalid.
|
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Last updated 2023-05-25 UTC.
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