How to perform tf.image.per_image_standardization on a batch of images in tensorflow

Question

I would like to know how to perform image whitening on a batch of images.

According to the documentation in https://www.tensorflow.org/api_docs/python/tf/image/per_image_standardization, it is said that tf.image.per_image_standardization takes as input a 3D tensor, that is an image, of shape: [height, width, channels].

Is it a missing feature or there is a different method?

Any help is much appreciated.

Rosiarosicrucian

usually, Tf pipelines involves preprocessing on single image and queuing them to generate batches. For example: github.com/tensorflow/models/blob/master/inception/inception/… – Monatomic

@HarshaPokkalla, link rot! – Dorset

Answer 1

This is how to perform this operation on a batch of images.

tf.map_fn(lambda frame: tf.image.per_image_standardization(frame), frames)

Rosiarosicrucian

Can you explain your solution? What does the function return? What is lambda, frame and frames? – Earplug

tf.image.per_image_standardization takes takes as input 1 image at a time. tf.map_fn is used to apply a function on every instance of a batch. The batch here is frames and each instance of that is a frame. As for the lambda, this is pythonic way to create a callable method; which the tf.map_fn requires as input. Hope this help – Rosiarosicrucian

You can now give the function directly a batch of images in tf 1.14 before it was working only on single images. – Fuliginous