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Randomly crops a tensor to a given size.
tf.image.random_crop(
value, size, seed=None, name=None
)
Used in the notebooks
| Used in the tutorials |
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Slices a shape size portion out of value at a uniformly chosen offset.
Requires value.shape >= size.
If a dimension should not be cropped, pass the full size of that dimension.
For example, RGB images can be cropped with
size = [crop_height, crop_width, 3].
Example usage:
image = [[1, 2, 3], [4, 5, 6]]result = tf.image.random_crop(value=image, size=(1, 3))result.shape.as_list()[1, 3]
For producing deterministic results given a seed value, use
tf.image.stateless_random_crop. Unlike using the seed param with
tf.image.random_* ops, tf.image.stateless_random_* ops guarantee the same
results given the same seed independent of how many times the function is
called, and independent of global seed settings (e.g. tf.random.set_seed).
Args | |
|---|---|
value
|
Input tensor to crop. |
size
|
1-D tensor with size the rank of value.
|
seed
|
Python integer. Used to create a random seed. See
tf.random.set_seed
for behavior.
|
name
|
A name for this operation (optional). |
Returns | |
|---|---|
A cropped tensor of the same rank as value and shape size.
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