loaddata.py

from keras.preprocessing.image import ImageDataGenerator

train_data_dir = 'face//train//'
validation_data_dir = 'face//validation//'

# Let's use some data augmentaiton 
train_datagen = ImageDataGenerator(
      rescale=1./255,
      rotation_range=45,
      width_shift_range=0.3,
      height_shift_range=0.3,
      horizontal_flip=True,
      fill_mode='nearest')
 
validation_datagen = ImageDataGenerator(rescale=1./255)
 
# set our batch size (typically on most mid tier systems we'll use 16-32)
batch_size = 64
 
train_generator = train_datagen.flow_from_directory(
        train_data_dir,
        target_size=(img_rows, img_cols),
        batch_size=batch_size,
        class_mode='categorical')
 
validation_generator = validation_datagen.flow_from_directory(
        validation_data_dir,
        target_size=(img_rows, img_cols),
        batch_size=batch_size,
        class_mode='categorical')