tf.image.pad_to_bounding_box

Pad image with zeros to the specified height and width.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.image.pad_to_bounding_box

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)>

Args
image	4-D Tensor of shape [batch, height, width, channels] or 3-D Tensor of shape [height, width, channels].
offset_height	Number of rows of zeros to add on top.
offset_width	Number of columns of zeros to add on the left.
target_height	Height of output image.
target_width	Width of output image.

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.