How to convert input numpy data to tensorflow tf.data to train model in tensorfow?
You could try using the flow_from_directory() method on your ImageDataGenerator class, which does the augmentation - only a small change is necessary:
H = model.fit(
    aug.flow_from_directory(trainX, trainY, batch_size=BS),
    ...)

If you start using a tf.data.Dataset directly, you will get more control over how the data is read from disk (caching, number of threads etc.), but you will lose the easy image augmentation you get with the ImageDataGenerator.