Using ImageDataGenerator to read images form the directories

images.py

from keras.preprocessing.image import ImageDataGenerator

# Rescaling all images by 1/255
train_datagen = ImageDataGenerator(rescale=1./255)
test_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(
    directory=TRAIN_DIR,
    target_size=(150, 150), # Resizing all images to 150 x 150
    batch_size=20,
    class_mode='binary' # Since we are using binary_crossentropy, we need binary labels.
)

validation_generator = test_datagen.flow_from_directory(
    directory=VALIDATION_DIR,
    target_size=(150, 150),
    batch_size=20,
    class_mode='binary'
)