# W3cubDocs

/TensorFlow 2.4

Pad `image` with zeros to the specified `height` and `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.]]]
<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.