TensorFlow 1 version | View source on GitHub |
Randomly crops a tensor to a given size.
tf.image.random_crop(
value, size, seed=None, name=None
)
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 .
|