python - batch_size = x.shape[0] AttributeError : 'tuple' object has no attribute 'shape'

Question

此代码结合了图像和掩码以进行图像检测？
我该如何纠正该错误？

batch_size = x.shape[0] AttributeError: 'tuple' object has no attribute 'shape'

这是用于训练的代码:

train_datagen = ImageDataGenerator(
            rescale=1. / 255,
            shear_range=0.2,
            zoom_range=0.2,
            horizontal_flip=True)
train_datagen_1 = ImageDataGenerator(
            rescale=1. / 255,
            shear_range=0.2,
            zoom_range=0.2,
            horizontal_flip=True)


train_generator = train_datagen.flow_from_directory(
            train_data_dir,
            target_size=(200, 150),
            batch_size=1
          )
train_generator_1= train_datagen_1.flow_from_directory(
            train_data_dir_1,
            target_size=(200, 150),
            batch_size=1)
train_generator_2 = zip( train_generator, train_generator_1)

model.fit_generator(
            train_generator_2,
            steps_per_epoch=nb_train_samples // batch_size,
            epochs=50)

这是我正在使用的模型:

model = Sequential() 
model.add(Conv2D(32, (3, 3), input_shape=(200, 150, 3))) 
model.add(Activation('relu')) 
model.add(MaxPooling2D(pool_size=(2, 2))) 
model.add(Flatten()) 
model.add(Dense(20)) model.add(Activation('relu')) 
model.add(Dropout(0.5)) 
model.add(Dense(90000)) 
model.add(Activation('sigmoid')) 
model.compile(loss='mse', optimizer='rmsprop', metrics=['accuracy'])

Answer 1

所选答案不准确。代码失败的原因不是因为元组属于 ((input1,output1), (input2,output2)), ...)，而是因为它们属于 类型>(((input1, class1), (input2, class2), ...), ((output1, class1), (output2, class2), ...))。

您可以通过简单地将 class_mode=None 添加到您的 flow_from_directory 调用来解决您的问题。