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.
|
View source on GitHub