View source on GitHub |
Pad image
with zeros to the specified height
and width
.
tf.image.pad_to_bounding_box(
image, offset_height, offset_width, target_height, target_width
)
Adds offset_height
rows of zeros on top, offset_width
columns of
zeros on the left, and then pads the image on the bottom and right
with zeros until it has dimensions target_height
, target_width
.
This op does nothing if offset_*
is zero and the image already has size
target_height
by target_width
.
Usage Example:
x = [[[1., 2., 3.],
[4., 5., 6.]],
[[7., 8., 9.],
[10., 11., 12.]]]
padded_image = tf.image.pad_to_bounding_box(x, 1, 1, 4, 4)
padded_image
<tf.Tensor: shape=(4, 4, 3), dtype=float32, numpy=
array([[[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.]],
[[ 0., 0., 0.],
[ 1., 2., 3.],
[ 4., 5., 6.],
[ 0., 0., 0.]],
[[ 0., 0., 0.],
[ 7., 8., 9.],
[10., 11., 12.],
[ 0., 0., 0.]],
[[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.]]], dtype=float32)>
Returns | |
---|---|
If image was 4-D, a 4-D float Tensor of shape
[batch, target_height, target_width, channels]
If image was 3-D, a 3-D float Tensor of shape
[target_height, target_width, channels]
|
Raises | |
---|---|
ValueError
|
If the shape of image is incompatible with the offset_* or
target_* arguments, or either offset_height or offset_width is
negative.
|