tfa.image.translate

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.