tfm.vision.preprocess_ops.normalize_image
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Normalizes the image to zero mean and unit variance.
tfm.vision.preprocess_ops.normalize_image(
image: tf.Tensor,
offset: Sequence[float] = tfm.vision.preprocess_ops.MEAN_NORM,
scale: Sequence[float] = tfm.vision.preprocess_ops.STDDEV_NORM
) -> tf.Tensor
If the input image dtype is float, it is expected to either have values in
[0, 1) and offset is MEAN_NORM, or have values in [0, 255] and offset is
MEAN_RGB.
Args |
|---|
image
|
A tf.Tensor in either (1) float dtype with values in range [0, 1) or
[0, 255], or (2) int type with values in range [0, 255].
|
offset
|
A tuple of mean values to be subtracted from the image.
|
scale
|
A tuple of normalization factors.
|
Returns |
|---|
|
A normalized image tensor.
|
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Last updated 2024-02-02 UTC.
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View source on GitHub