tf.image.stateless_random_jpeg_quality

Deterministically radomize jpeg encoding quality for inducing jpeg noise.

tf.image.stateless_random_jpeg_quality(
    image, min_jpeg_quality, max_jpeg_quality, seed
)

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).

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 = [[[1, 2, 3],
      [4, 5, 6]],
     [[7, 8, 9],
      [10, 11, 12]]]
x_uint8 = tf.cast(x, tf.uint8)
seed = (1, 2)
tf.image.stateless_random_jpeg_quality(x_uint8, 75, 95, seed)
<tf.Tensor: shape=(2, 2, 3), dtype=uint8, numpy=
array([[[ 0,  4,  5],
        [ 1,  5,  6]],
       [[ 5,  9, 10],
        [ 5,  9, 10]]], dtype=uint8)>

Args
`image`	3D image. Size of the last dimension must be 1 or 3.
`min_jpeg_quality`	Minimum jpeg encoding quality to use.
`max_jpeg_quality`	Maximum jpeg encoding quality to use.
`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 `min_jpeg_quality` or `max_jpeg_quality` is invalid.

tf.image.stateless_random_jpeg_quality

Usage Example:

Args

Returns

Raises