tf.image.stateless_random_saturation
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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 .
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.image.stateless_random_saturation\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/image_ops_impl.py#L3058-L3105) |\n\nAdjust the saturation of RGB images by a random factor deterministically. \n\n tf.image.stateless_random_saturation(\n image, lower, upper, seed=None\n )\n\nEquivalent to `adjust_saturation()` but uses a `saturation_factor` randomly\npicked in the interval `[lower, upper)`.\n\nGuarantees the same results given the same `seed` independent of how many\ntimes the function is called, and independent of global seed settings (e.g.\n[`tf.random.set_seed`](../../tf/random/set_seed)).\n\n#### Usage Example:\n\n x = [[[1.0, 2.0, 3.0],\n [4.0, 5.0, 6.0]],\n [[7.0, 8.0, 9.0],\n [10.0, 11.0, 12.0]]]\n seed = (1, 2)\n tf.image.stateless_random_saturation(x, 0.5, 1.0, seed)\n \u003ctf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=\n array([[[ 1.1559395, 2.0779698, 3. ],\n [ 4.1559396, 5.07797 , 6. ]],\n [[ 7.1559396, 8.07797 , 9. ],\n [10.155939 , 11.07797 , 12. ]]], dtype=float32)\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|-----------------------------------------------------------------------------------------------------------------------------------------------|\n| `image` | RGB image or images. The size of the last dimension must be 3. |\n| `lower` | float. Lower bound for the random saturation factor. |\n| `upper` | float. Upper bound for the random saturation factor. |\n| `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.) |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| Adjusted image(s), same shape and DType as `image`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|----------------------------------------|\n| `ValueError` | if `upper \u003c= lower` or if `lower \u003c 0`. |\n\n\u003cbr /\u003e"]]