model.py 文件源码

def __init__(self, input_shape, classes, model_save_filepath):        
        self.model_save_filepath = model_save_filepath  

        self.neptune_organizer = None

        self.old_session = K.get_session()
        session = tf.Session('')
        K.set_session(session)
        K.set_learning_phase(1)

        face_input = Input(batch_shape=(None,) + (input_shape))

        pretrained_model = VGG16(input_tensor=face_input, 
                                 weights='imagenet', 
                                 include_top=False)
        x = pretrained_model.get_layer('block4_pool').output

        x = Flatten(name='flatten')(x)
        x = Dense(256, activation='relu', name='fc1')(x)
        x = Dense(256, activation='relu', name='fc2')(x)
        output = Dense(classes, activation='softmax', name='predictions')(x)

        self.facenet = Model(face_input, output)
        self.facenet.compile(optimizer='adam',
                             loss='categorical_crossentropy',
                             metrics=['accuracy'])
        self.facenet.summary()

        self.datagen = ImageDataGenerator(rotation_range=5,
                                          horizontal_flip=False, 
                                          vertical_flip=True)