I'm working on an astronomical images classification project and I'm currently using keras to build CNNs.
I'm trying to build a preprocessing pipeline to augment my dataset with keras/tensorflow layers. To keep things simple I would like to implement random transformations of the dihedral group (i.e., for square images, 90-degrees rotations and flips), but it seems that tf.keras.preprocessing.image.random_rotation only allows a random degree over a continuous range of choice following a uniform distribution.
I was wondering whether there is a way to instead choose from a list of specified degrees, in my case [0, 90, 180, 270].