View source on GitHub |
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
).
Usage Example:
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)>
Returns | |
---|---|
Adjusted image(s), same shape and DType as image .
|
Raises | |
---|---|
ValueError
|
if upper <= lower or if lower < 0 .
|