Transpose image(s) by swapping the height and width dimension.
tf.image.transpose(
image, name=None
)
Usage Example:
x = [[[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0]],
[[7.0, 8.0, 9.0],
[10.0, 11.0, 12.0]]]
tf.image.transpose(x)
<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=
array([[[ 1., 2., 3.],
[ 7., 8., 9.]],
[[ 4., 5., 6.],
[10., 11., 12.]]], dtype=float32)>
Args |
image
|
4-D Tensor of shape [batch, height, width, channels] or 3-D Tensor
of shape [height, width, channels] .
|
name
|
A name for this operation (optional).
|
Returns |
If image was 4-D, a 4-D float Tensor of shape
[batch, width, height, channels]
If image was 3-D, a 3-D float Tensor of shape
[width, height, channels]
|
Raises |
ValueError
|
if the shape of image not supported.
|
Usage Example:
image = [[[1, 2], [3, 4]],
[[5, 6], [7, 8]],
[[9, 10], [11, 12]]]
image = tf.constant(image)
tf.image.transpose(image)
<tf.Tensor: shape=(2, 3, 2), dtype=int32, numpy=
array([[[ 1, 2],
[ 5, 6],
[ 9, 10]],
[[ 3, 4],
[ 7, 8],
[11, 12]]], dtype=int32)>