ML Community Day is November 9! Join us for updates from TensorFlow, JAX, and more Learn more

tf.image.transpose

Transpose image(s) by swapping the height and width dimension.

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)>

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).

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]

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)>