python-kerasHow do I use Python and Keras to create a VGG16 model?

Using Python and Keras, you can create a VGG16 model to classify images. To do this, you will need to import the necessary libraries, define the model layers, and compile the model.

Example code

from keras.applications import VGG16

# load model
model = VGG16(include_top=True, weights='imagenet')

# freeze all layers
for layer in model.layers:
    layer.trainable = False

# compile model
model.compile(optimizer='rmsprop', loss='categorical_crossentropy')

The code above imports the VGG16 model from the Keras applications library, loads the model with the ImageNet weights, and freezes all of the layers. It then compiles the model using the RMSprop optimizer and categorical cross entropy loss function.

Code explanation

1. from keras.applications import VGG16: imports the VGG16 model from the Keras applications library.
2. model = VGG16(include_top=True, weights='imagenet'): loads the VGG16 model with the ImageNet weights.
3. for layer in model.layers: layer.trainable = False: freezes all of the layers in the model.
4. model.compile(optimizer='rmsprop', loss='categorical_crossentropy'): compiles the model using the RMSprop optimizer and categorical cross entropy loss function.

Helpful links

• Keras Applications Documentation
• VGG16 Documentation

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