Getting a list of all known classes of vgg-16 in keras

I think if you do something like this:

vgg16 = keras.applications.vgg16.VGG16(include_top=True,
                               weights='imagenet',
                               input_tensor=None,
                               input_shape=None,
                               pooling=None,
                               classes=1000)

vgg16.decode_predictions(np.arange(1000), top=1000)

Substitute your prediction array for np.arange(1000). Untested code so far.

Link to training labels here I think: http://image-net.org/challenges/LSVRC/2014/browse-synsets

You could use decode_predictions and pass the total number of classes in the top=1000 parameter (only its default value is 5).

Or you could look at how Keras does this internally: It downloads the file imagenet_class_index.json (and usually caches it in ~/.keras/models/). This is a simple json file containing all class labels.