tf.image.transpose

TensorFlow 1 version View source on GitHub

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)>