Python 如何在自定义数据生成器中实现重缩放？

我使用

tf.keras.utils.Sequence

：（）创建了一个自定义的

数据生成器。
这是定制的
数据生成器
：

# Here, `x_set` is list of path to the images
# and `y_set` are the associated classes.

class DataGenerator(Sequence):

    def __init__(self, x_set, y_set, batch_size):
        self.x, self.y = x_set, y_set
        self.batch_size = batch_size

    def __len__(self):
        return math.ceil(len(self.x) / self.batch_size)

    def __getitem__(self, idx):
        batch_x = self.x[idx * self.batch_size:(idx + 1) *
        self.batch_size]
        batch_x = np.array(batch_x)
        batch_x = batch_x*1/255
        batch_y = self.y[idx * self.batch_size:(idx + 1) *
        self.batch_size]

        return np.array([
            resize(imread(file_name), (64, 128))
               for file_name in batch_x]), np.array(batch_y)

model.fit_generator(generator=training_generator,
                    validation_data=validation_generator,
                    steps_per_epoch = num_train_samples // 128,
                    validation_steps = num_val_samples // 128,
                    epochs = 10)

x_集
是指向我的图像的路径列表，
y_集
是关联的类。
现在，我想添加一个函数，通过将图像的每个像素乘以
rescale=1./255
来重新缩放图像，就像在
ImageDataGenerator
类中一样：

当我将此代码应用于
型号时。安装发电机
：

# Here, `x_set` is list of path to the images
# and `y_set` are the associated classes.

class DataGenerator(Sequence):

    def __init__(self, x_set, y_set, batch_size):
        self.x, self.y = x_set, y_set
        self.batch_size = batch_size

    def __len__(self):
        return math.ceil(len(self.x) / self.batch_size)

    def __getitem__(self, idx):
        batch_x = self.x[idx * self.batch_size:(idx + 1) *
        self.batch_size]
        batch_x = np.array(batch_x)
        batch_x = batch_x*1/255
        batch_y = self.y[idx * self.batch_size:(idx + 1) *
        self.batch_size]

        return np.array([
            resize(imread(file_name), (64, 128))
               for file_name in batch_x]), np.array(batch_y)

model.fit_generator(generator=training_generator,
                    validation_data=validation_generator,
                    steps_per_epoch = num_train_samples // 128,
                    validation_steps = num_val_samples // 128,
                    epochs = 10)

我得到这个错误：

---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
<ipython-input-62-571a868b2d2a> in <module>()
      3                     steps_per_epoch = num_train_samples // 128,
      4                     validation_steps = num_val_samples // 128,
----> 5                     epochs = 10)

8 frames
<ipython-input-54-d98c3b0c7c56> in __getitem__(self, idx)
     15         self.batch_size]
     16         batch_x = np.array(batch_x)
---> 17         batch_x = batch_x*1/255
     18         batch_y = self.y[idx * self.batch_size:(idx + 1) *
     19         self.batch_size]

UFuncTypeError: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U77'), dtype('<U77')) -> dtype('<U77')

---------------------------------------------------------------------------
UFuncTypeError回溯（最近一次调用上次）
在（）
每个历元3个步骤=num列样本//128，
4个验证步骤=num\u val\u样本//128，
---->5个时代=10个）
8帧
in _uGetItem_uuu（self，idx）
15.自身批次大小]
16批次x=np.数组（批次x）
--->17批次x=批次x*1/255
18批次y=self.y[idx*self.batch_大小：（idx+1）*
19.自身批次大小]
UFuncTypeError:ufunc“multiply”不包含具有签名匹配类型的循环（数据类型（“请以这种方式尝试

class DataGenerator(Sequence):

    def __init__(self, x_set, y_set, batch_size):
        self.x, self.y = x_set, y_set
        self.batch_size = batch_size

    def __len__(self):
        return math.ceil(len(self.x) / self.batch_size)

    def __getitem__(self, idx):
        batch_x = self.x[idx*self.batch_size : (idx + 1)*self.batch_size]
        batch_x = np.array([resize(imread(file_name), (64, 128)) for file_name in batch_x])
        batch_x = batch_x * 1./255
        batch_y = self.y[idx*self.batch_size : (idx + 1)*self.batch_size]
        batch_y = np.array(batch_y)

        return batch_x, batch_y

batch_x*1./255？我必须在哪里实现此代码？如果定义batch_x或在batch_x=batch_x*1/255下面的行中，则我得到：
TypeError:不支持的操作数类型对于/：“list”和“int”
要进行此批处理，x必须是一个数组，非常感谢您！它可以工作。但是，它确实很慢，我不知道。但是它以前已经很慢了。。。