How to merge two DirectoryIterator?

Hi, I’m looking at the example here: https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html

They create 3 iterators: for train, validation and test.

test_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(
        'data/train',  # this is the target directory
        target_size=(150, 150),  # all images will be resized to 150x150
        batch_size=batch_size,
        class_mode='binary')  # since we use binary_crossentropy loss, we need binary labels

validation_generator = test_datagen.flow_from_directory(
        'data/validation',
        target_size=(150, 150),
        batch_size=batch_size,
        class_mode='binary')

My question is whether it’s possible to merge\combine train_generator with validation_generator to a single generator that contains images from both train and validation folder.

THX

[Dref360]

Iterators are Sequence. You can create you own Sequence

from keras.utils import Sequence

flow1 = train_datagen.flow_from_directory(...)
flow2 = train_datagen.flow_from_directory(...)

class MySequence(Sequence):
    def __init__(self, seq1, seq2):
        self.seq1, self.seq2 = seq1, seq2
    def __len__(self):
        return len(self.seq1)

    def __getitem(self, idx):
        x1, y1 = self.seq1[idx]
        x2, y2 = self.seq2[idx]
        return [x1, x2], [y1, y2]

my_seq = MySequence(flow1, flow2)
model.fit_generator(my_seq, ...)

[vipuljain-17]

Did you ever get the solution to this problem?