Reorder channel layer for smooth native RGB - BGR

This is a commonly performed operation in image processing making it a good fit for keras-cv. While this is not a super complicated operation (it’s really just a lambda into a tf.gather) the resulting code is more readable. Let’s include this in keras-cv.

Originally discussed here: https://github.com/keras-team/keras/issues/15705

Re the design of the layer signature…

The current proposal is to implement a layer that looks like this:

rgb2bgr_layer = tf.keras.layers.ReorderChannel(order=[2, 1, 0], axis=-1)

Perhaps we actually may want to use a einsum inspired syntax, such as:

rgb2bgr_layer = tf.keras.layers.ReorderChannel('rgb->bgr', axis=-1)

This would be really readable to anyone stumbling upon a new codebase, and generalizes quite well to any number of channels.

Please feel free to comment below with any additional thoughts

[LukeWood]

I’d be fond of the API:

rgb2bgr_layer = keras_cv.layers.ReorderChannel('rgb->bgr', axis=-1)

I think we could include this if someone wanted to contribute it.

[bhack]

This seems only about reordering but more in general we have many colorspace conversions in:

https://github.com/tensorflow/io/blob/v0.20.0/tensorflow_io/python/experimental/color_ops.py#L20