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.
|
View source on GitHub