|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/ops/image_ops_impl.py#L2873-L2926) | 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`](https://www.tensorflow.org/api_docs/python/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 = tf.constant([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], dtype=tf.uint8) seed = (1, 2) tf.image.stateless_random_jpeg_quality(x, 75, 95, seed)


| ## 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. |