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tf.image.stateless_random_saturation

Adjust the saturation of RGB images by a random factor deterministically.

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)>

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.)

Adjusted image(s), same shape and DType as image.

ValueError if upper <= lower or if lower < 0.