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tfa.image.translate
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Translate image(s) by the passed vectors(s).
@tf.function
tfa.image.translate(
images: tfa.types.TensorLike
,
translations: tfa.types.TensorLike
,
interpolation: str = 'nearest',
fill_mode: str = 'constant',
name: Optional[str] = None,
fill_value: tfa.types.TensorLike
= 0.0
) -> tf.Tensor
Args |
images
|
A tensor of shape
(num_images, num_rows, num_columns, num_channels) (NHWC),
(num_rows, num_columns, num_channels) (HWC), or
(num_rows, num_columns) (HW). The rank must be statically known (the
shape is not TensorShape(None) ).
|
translations
|
A vector representing [dx, dy] or (if images has rank 4)
a matrix of length num_images, with a [dx, dy] vector for each image
in the batch.
|
interpolation
|
Interpolation mode. Supported values: "nearest",
"bilinear".
|
fill_mode
|
Points outside the boundaries of the input are filled according
to the given mode (one of {'constant', 'reflect', 'wrap', 'nearest'} ).
- reflect:
(d c b a | a b c d | d c b a)
The input is extended by reflecting about the edge of the last pixel.
- constant:
(k k k k | a b c d | k k k k)
The input is extended by filling all values beyond the edge with the
same constant value k = 0.
- wrap:
(a b c d | a b c d | a b c d)
The input is extended by wrapping around to the opposite edge.
- nearest:
(a a a a | a b c d | d d d d)
The input is extended by the nearest pixel.
|
fill_value
|
a float represents the value to be filled outside the
boundaries when fill_mode is "constant".
|
name
|
The name of the op.
|
Returns |
Image(s) with the same type and shape as images , translated by the
given vector(s). Empty space due to the translation will be filled with
zeros.
|
Raises |
TypeError
|
If images is an invalid type.
|
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Last updated 2023-05-25 UTC.
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