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` . |

© 2020 The TensorFlow Authors. All rights reserved.

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