コード例 #1
0
ファイル: train.py プロジェクト: yangx3/CS463-Group11
def train(nb_epoch, freeze_layers_number):
    model = util.get_model_class_instance(
        class_weight=util.get_class_weight(config.train_dir),
        nb_epoch=nb_epoch,
        freeze_layers_number=freeze_layers_number)
    model.train()
    print('Training is finished!')
コード例 #2
0
def train():
    model = util.get_model_class_instance(
        class_weight=util.get_class_weight(config.train_dir),
        nb_epoch=args.nb_epoch,
        batch_size=args.batch_size,
        freeze_layers_number=args.freeze_layers_number)
    model.train()
    print('Training is finished!')
コード例 #3
0
def train():
    model = util.get_model_class_instance(
        class_weight=util.get_class_weight(config.train_dir),
        nb_epoch=args.nb_epoch,
        batch_size=args.batch_size,
        freeze_layers_number=args.freeze_layers_number)
    model.train()
    print('Training is finished!')
コード例 #4
0
ファイル: train.py プロジェクト: marc45/keras-oxford102
def train(nb_epoch,
          freeze_layers_number,
          auto_load_finetune=False,
          visual=False):
    model = util.get_model_class_instance(
        class_weight=util.get_class_weight(config.train_dir),
        nb_epoch=nb_epoch,
        freeze_layers_number=freeze_layers_number)
    model.train(auto_load_fine_tune=auto_load_finetune, visual=visual)
    print('Training is finished!')
コード例 #5
0
def run():
    model = util.get_model_class_instance(
        class_weight=util.get_class_weight(config.train_dir),
        nb_epoch=args.nb_epoch,
        batch_size=args.batch_size,
        freeze_layers_number=args.freeze_layers_number)

    #config.train_dir = 'data/sorted/test/'
    #model.load()
    #model.test()
    model.train()
    #model.extract()
    model.evaluate()

    print('Training is finished!')
コード例 #6
0
    try:
        args = parse_args()

        if args.data_dir:
            config.data_dir = args.data_dir
            config.set_paths()
        if args.model:
            config.model = args.model

        util.lock()
        util.override_keras_directory_iterator_next()
        util.set_classes_from_train_dir()
        util.set_samples_info()
        if not os.path.exists(config.trained_dir):
            os.mkdir(config.trained_dir)

        class_weight = util.get_class_weight(config.train_dir)
        # TODO: create class instance without dynamic module import
        model = util.get_model_class_instance(
            class_weight=class_weight,
            nb_epoch=args.nb_epoch,
            freeze_layers_number=args.freeze_layers_number)
        model.train()
        print('Training is finished!')
    except (KeyboardInterrupt, SystemExit):
        util.unlock()
    except Exception as e:
        print(e)
        print(traceback.format_exc())
    util.unlock()