View source on GitHub |
Adjust the saturation of RGB images by a random factor.
tf.image.random_saturation(
image, lower, upper, seed=None
)
Equivalent to adjust_saturation()
but uses a saturation_factor
randomly
picked in the interval [lower, upper)
.
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]]]
tf.image.random_saturation(x, 5, 10)
<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=
array([[[ 0. , 1.5, 3. ],
[ 0. , 3. , 6. ]],
[[ 0. , 4.5, 9. ],
[ 0. , 6. , 12. ]]], dtype=float32)>
For producing deterministic results given a seed
value, use
tf.image.stateless_random_saturation
. 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).
Returns | |
---|---|
Adjusted image(s), same shape and DType as image .
|
Raises | |
---|---|
ValueError
|
if upper <= lower or if lower < 0 .
|