RandomTranslation classtf_keras.layers.RandomTranslation(
height_factor,
width_factor,
fill_mode="reflect",
interpolation="bilinear",
seed=None,
fill_value=0.0,
**kwargs
)
A preprocessing layer which randomly translates images during training.
This layer will apply random translations to each image during training,
filling empty space according to fill_mode.
Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]) and
of integer or floating point dtype. By default, the layer will output
floats.
For an overview and full list of preprocessing layers, see the preprocessing guide.
Arguments
height_factor=(-0.2, 0.3) results in an output shifted by a random
amount in the range [-20%, +30%]. height_factor=0.2 results in an
output height shifted by a random amount in the range [-20%, +20%].width_factor=(-0.2, 0.3) results in an output shifted left by 20%,
and shifted right by 30%. width_factor=0.2 results
in an output height shifted left or right by 20%.{"constant", "reflect", "wrap", "nearest"}).(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.(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.(a b c d | a b c d | a b c d) The input is extended by
wrapping around to the opposite edge.(a a a a | a b c d | d d d d) The input is extended by
the nearest pixel."nearest",
"bilinear".fill_mode="constant".Input shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.
Output shape
3D (unbatched) or 4D (batched) tensor with shape:
(..., height, width, channels), in "channels_last" format.