OCR

train_model.py

def step_decay(epoch):
    initial_learning_rate = 0.001
    dropEvery = 10
    factor = 0.5
    lr = initial_learning_rate*(factor**np.floor((1 + epoch)/dropEvery))
    return float(lr)

checkpoint = ModelCheckpoint('maths_symbol_and_digits_recognition.h5', 
                             monitor='val_loss', save_best_only=True, 
                             verbose=1, mode='min')

callbacks = [checkpoint, LearningRateScheduler(step_decay)]

aug = ImageDataGenerator(zoom_range=0.1,
                         width_shift_range=0.05,
                         height_shift_range=0.05)
hist = model.fit(aug.flow(X_train, Y_train, batch_size=128), 
                 batch_size=128, epochs=100, 
                 validation_data=(X_test, Y_test))