Keras has a good batch generator named keras.utils.sequence() that helps you customize batch creation with great flexibility. In fact, with keras.utils.sequence() one can design the whole epoch pipeline. We are going to use this utility in this regression problem to get accustomed to this utility. For the transfer learning problem we can design a generator class using keras.utils.sequence() as follows:
class DataGenerator(keras.utils.Sequence): 'Generates data for Keras' def __init__(self,files,labels,batch_size=32,n_classes=5,dim=(224,224,3),shuffle=True): 'Initialization' self.labels = labels self.files = files self.batch_size = batch_size self.n_classes = n_classes self.dim = dim self.shuffle ...
