View source on GitHub |
Randomly changes jpeg encoding quality for inducing jpeg noise.
tf.image.random_jpeg_quality(
image, min_jpeg_quality, max_jpeg_quality, seed=None
)
min_jpeg_quality
must be in the interval [0, 100]
and less than
max_jpeg_quality
.
max_jpeg_quality
must be in the interval [0, 100]
.
Usage Example:
x = tf.constant([[[1, 2, 3],
[4, 5, 6]],
[[7, 8, 9],
[10, 11, 12]]], dtype=tf.uint8)
tf.image.random_jpeg_quality(x, 75, 95)
<tf.Tensor: shape=(2, 2, 3), dtype=uint8, numpy=...>
For producing deterministic results given a seed
value, use
tf.image.stateless_random_jpeg_quality
. Unlike using the seed
param
with tf.image.random_*
ops, tf.image.stateless_random_*
ops guarantee 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).
Returns | |
---|---|
Adjusted image(s), same shape and DType as image .
|
Raises | |
---|---|
ValueError
|
if min_jpeg_quality or max_jpeg_quality is invalid.
|