Randomly crops a tensor to a given size in a deterministic manner.
tf.image.stateless_random_crop( value, size, seed, 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]
.
Guarantees 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
).
image = [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]] seed = (1, 2) tf.image.stateless_random_crop(value=image, size=(1, 2, 3), seed=seed) <tf.Tensor: shape=(1, 2, 3), dtype=int32, numpy= array([[[1, 2, 3], [4, 5, 6]]], dtype=int32)>
Args | |
---|---|
value | Input tensor to crop. |
size | 1-D tensor with size the rank of value . |
seed | A shape [2] Tensor, the seed to the random number generator. Must have dtype int32 or int64 . (When using XLA, only int32 is allowed.) |
name | A name for this operation (optional). |
Returns | |
---|---|
A cropped tensor of the same rank as value and shape size . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/image/stateless_random_crop