tf.image.random_flip_up

TensorFlow 1 version

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Randomly changes jpeg encoding quality for inducing jpeg noise.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.image.random_jpeg_quality

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 = [[[1.0, 2.0, 3.0],
      [4.0, 5.0, 6.0]],
    [[7.0, 8.0, 9.0],
      [10.0, 11.0, 12.0]]]
tf.image.random_jpeg_quality(x, 75, 95)
<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=...>

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`	An operation-specific seed. It will be used in conjunction with the graph-level seed to determine the real seeds that will be used in this operation. Please see the documentation of set_random_seed for its interaction with the graph-level random seed.

Returns
Adjusted image(s), same shape and DType as `image`.

Raises
`ValueError`	if `min_jpeg_quality` or `max_jpeg_quality` is invalid.

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tf.image / random_flip_up_down

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Usage Example:

Args

Returns

Raises