Add kernel for image standardization.

[annxingyuan]

We often process images in the following way before feeding them to models:

tf.mul(tf.sub(inputImage.toFloat().div(255), 0.5), 2)

This could be achieved with a single kernel, following TensorFlow's example: https://www.tensorflow.org/api_docs/python/tf/image/per_image_standardization

[annxingyuan]

@dsmilkov Reading over https://github.com/tensorflow/tensorflow/blob/r2.0/tensorflow/python/ops/image_ops_impl.py#L1477-L1519, it looks like the TensorFlow op per_image_standardization properly normalizes by subtracting the input mean / dividing by the standard deviation, whereas in our case we just want to scale the input to [-1, 1].

It would still be great to combine these ops into a single kernel for models like Blazeface - what do you think about adding this as a custom op on a per-model basis rather than to the library?

[dsmilkov]

Good point. In that case, custom op on a per-model basis SGTM (we can't add it to official API until TF Python has it)

[annxingyuan]

Perhaps this should be part of the future models utilities library.

[gaikwadrahul8]

Hi, @annxingyuan

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