Split data directory into training and test directory with sub directory structure preserved

Question

I am interested in using ImageDataGenerator in Keras for data augmentation. But it requires that training and validation directories with sub directories for classes be fed in separately as below (this is from Keras documentation). I have a single directory with 2 subdirectories for 2 classes (Data/Class1 and Data/Class2). How do I randomly split this into training and validation directories

    train_datagen = ImageDataGenerator(
    rescale=1./255,
    shear_range=0.2,
    zoom_range=0.2,
    horizontal_flip=True)

    test_datagen = ImageDataGenerator(rescale=1./255)

    train_generator = train_datagen.flow_from_directory(
    'data/train',
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary')

   validation_generator = test_datagen.flow_from_directory(
    'data/validation',
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary')

   model.fit_generator(
    train_generator,
    steps_per_epoch=2000,
    epochs=50,
    validation_data=validation_generator,
    validation_steps=800)

I am interested in re-running my algorithm multiple times with random training and validation data splits.

Answer 1

Thank you guys! I was able to write my own function to create training and test data sets. Here's the code for anyone who's looking.

import os
source1 = "/source_dir"
dest11 = "/dest_dir"
files = os.listdir(source1)
import shutil
import numpy as np
for f in files:
    if np.random.rand(1) < 0.2:
        shutil.move(source1 + '/'+ f, dest11 + '/'+ f)