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.