tf.image.non_max_suppression_with

TensorFlow 1 version

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Linearly scales each image in image to have mean 0 and variance 1.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.image.per_image_standardization

tf.image.per_image_standardization(
    image
)

For each 3-D image x in image, computes (x - mean) / adjusted_stddev, where

mean is the average of all values in x
adjusted_stddev = max(stddev, 1.0/sqrt(N)) is capped away from 0 to protect against division by 0 when handling uniform images
- N is the number of elements in x
- stddev is the standard deviation of all values in x

Args
`image`	An n-D Tensor with at least 3 dimensions, the last 3 of which are the dimensions of each image.

Returns
A `Tensor` with the same shape and dtype as `image`.

Raises
`ValueError`	if the shape of 'image' is incompatible with this function.

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tf.image / non_max_suppression_with_scores

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Args

Returns

Raises