Model_MobileNet.py

from keras.applications.mobilenet import MobileNet
from keras.models import Model
from keras.layers import Dense, GlobalAveragePooling2D

# parameters for architecture
input_shape = (224, 224, 3)
num_classes = 6
conv_size = 32

# parameters for training
batch_size = 32
num_epochs = 20

# load MobileNet from Keras
MobileNet_model = MobileNet(include_top=False, input_shape=input_shape)

# add custom Layers
x = MobileNet_model.output
x = GlobalAveragePooling2D()(x)
x = Dense(512, activation="relu")(x)
Custom_Output = Dense(num_classes, activation='softmax')(x)

# define the input and output of the model
model = Model(inputs = MobileNet_model.input, outputs = Custom_Output)
        
# compile the model
model.compile(loss='categorical_crossentropy',
                    optimizer='adam',
                    metrics=['accuracy'])

model.summary()

# train the model 
history = model.fit(x_train, y_train,
                    batch_size=batch_size,
                    epochs=num_epochs,
                    verbose=1,
                    validation_split=0.1)

which version of mobilenet is this? V1 or V2?
And is there a way to make it realtime like YOLO?

which version of mobilenet is this? V1 or V2?
And is there a way to make it realtime like YOLO?

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x_train was not declared.
So there is an error.