tf.image.random_flip_left_right
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Randomly flip an image horizontally (left to right).
tf.image.random_flip_left_right(
image, seed=None
)
With a 1 in 2 chance, outputs the contents of image flipped along the
second dimension, which is width. Otherwise output the image as-is.
When passing a batch of images, each image will be randomly flipped
independent of other images.
Example usage:
import numpy as np
image = np.array([[[1], [2]], [[3], [4]]])
tf.image.random_flip_left_right(image, 5).numpy().tolist()
[[[2], [1]], [[4], [3]]]
Randomly flip multiple images.
images = np.array(
... [
... [[[1], [2]], [[3], [4]]],
... [[[5], [6]], [[7], [8]]]
... ])
tf.image.random_flip_left_right(images, 6).numpy().tolist()
[[[[2], [1]], [[4], [3]]], [[[5], [6]], [[7], [8]]]]
Args |
|---|
image
|
4-D Tensor of shape [batch, height, width, channels] or 3-D Tensor
of shape [height, width, channels].
|
seed
|
A Python integer. Used to create a random seed. See
tf.compat.v1.set_random_seed for behavior.
|
Returns |
|---|
A tensor of the same type and shape as image.
|
Raises |
|---|
ValueError
|
if the shape of image not supported.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.image.random_flip_left_right\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/image/random_flip_left_right) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.2.0/tensorflow/python/ops/image_ops_impl.py#L363-L401) |\n\nRandomly flip an image horizontally (left to right).\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.random_flip_left_right`](/api_docs/python/tf/image/random_flip_left_right)\n\n\u003cbr /\u003e\n\n tf.image.random_flip_left_right(\n image, seed=None\n )\n\nWith a 1 in 2 chance, outputs the contents of `image` flipped along the\nsecond dimension, which is `width`. Otherwise output the image as-is.\nWhen passing a batch of images, each image will be randomly flipped\nindependent of other images.\n\n#### Example usage:\n\n import numpy as np\n\n image = np.array([[[1], [2]], [[3], [4]]])\n tf.image.random_flip_left_right(image, 5).numpy().tolist()\n [[[2], [1]], [[4], [3]]]\n\nRandomly flip multiple images.\n\u003e \u003e \u003e images = np.array(\n\u003e \u003e \u003e ... \\[\n\u003e \u003e \u003e ... \\[\\[\\[1\\], \\[2\\]\\], \\[\\[3\\], \\[4\\]\\]\\],\n\u003e \u003e \u003e ... \\[\\[\\[5\\], \\[6\\]\\], \\[\\[7\\], \\[8\\]\\]\\]\n\u003e \u003e \u003e ... \\])\n\u003e \u003e \u003e tf.image.random_flip_left_right(images, 6).numpy().tolist()\n\u003e \u003e \u003e \\[\\[\\[\\[2\\], \\[1\\]\\], \\[\\[4\\], \\[3\\]\\]\\], \\[\\[\\[5\\], \\[6\\]\\], \\[\\[7\\], \\[8\\]\\]\\]\\]\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| `seed` | A Python integer. Used to create a random seed. See [`tf.compat.v1.set_random_seed`](../../tf/compat/v1/set_random_seed) for behavior. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tensor of the same type and shape as `image`. ||\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"]]
TensorFlow 1 version
View source on GitHub