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.
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Raises | |
|---|---|
ValueError
|
if min_jpeg_quality or max_jpeg_quality is invalid.
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View source on GitHub