tf.image.transpose
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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)>
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.image.transpose\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/image_ops_impl.py#L788-L855) |\n\nTranspose image(s) by swapping the height and width dimension.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.image.transpose`](https://www.tensorflow.org/api_docs/python/tf/image/transpose), [`tf.compat.v1.image.transpose_image`](https://www.tensorflow.org/api_docs/python/tf/image/transpose)\n\n\u003cbr /\u003e\n\n tf.image.transpose(\n image, name=None\n )\n\n#### Usage Example:\n\n x = [[[1.0, 2.0, 3.0],\n [4.0, 5.0, 6.0]],\n [[7.0, 8.0, 9.0],\n [10.0, 11.0, 12.0]]]\n tf.image.transpose(x)\n \u003ctf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=\n array([[[ 1., 2., 3.],\n [ 7., 8., 9.]],\n [[ 4., 5., 6.],\n [10., 11., 12.]]], dtype=float32)\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|------------------------------------------------------------------------------------------------------------|\n| `image` | 4-D Tensor of shape `[batch, height, width, channels]` or 3-D Tensor of shape `[height, width, channels]`. |\n| `name` | A name for this operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| 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]` ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|----------------------------------------|\n| `ValueError` | if the shape of `image` not supported. |\n\n\u003cbr /\u003e\n\n#### Usage Example:\n\n image = [[[1, 2], [3, 4]],\n [[5, 6], [7, 8]],\n [[9, 10], [11, 12]]]\n image = tf.constant(image)\n tf.image.transpose(image)\n \u003ctf.Tensor: shape=(2, 3, 2), dtype=int32, numpy=\n array([[[ 1, 2],\n [ 5, 6],\n [ 9, 10]],\n [[ 3, 4],\n [ 7, 8],\n [11, 12]]], dtype=int32)\u003e"]]
View source on GitHub