Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tf.image.random_saturation

TensorFlow 1 version 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)> 

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: An operation-specific seed. It will be used in conjunction with the graph-level seed to determine the real seeds that will be used in this operation. Please see the documentation of set_random_seed for its interaction with the graph-level random seed.

Returns:

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

Raises:

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