Adjust the saturation of RGB images by a random factor deterministically.
tf.image.stateless_random_saturation( image, lower, upper, seed=None )
Equivalent to adjust_saturation()
but uses a saturation_factor
randomly picked in the interval [lower, upper)
.
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
).
x = [[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]] seed = (1, 2) tf.image.stateless_random_saturation(x, 0.5, 1.0, seed) <tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy= array([[[ 1.1559395, 2.0779698, 3. ], [ 4.1559396, 5.07797 , 6. ]], [[ 7.1559396, 8.07797 , 9. ], [10.155939 , 11.07797 , 12. ]]], dtype=float32)>
Args | |
---|---|
image | RGB image or images. The size of the last dimension must be 3. |
lower | float. Lower bound for the random saturation factor. |
upper | float. Upper bound for the random saturation factor. |
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.) |
Returns | |
---|---|
Adjusted image(s), same shape and DType as image . |
Raises | |
---|---|
ValueError | if upper <= lower or if lower < 0 . |
© 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_saturation