tf.image.stateless_random_saturation

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)>

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`.

tf.image.stateless_random_saturation

Usage Example:

Args

Returns

Raises