Use GAN discrimator for single-class classification

Hello,

i try to implement a neural network for classifying different defects for quality inspection. I want to use a single-class classification.

To accomplish this, i want to train a generative adversarial networks and use the discriminator for classification.

So i used the sunflower-example for implementing my first GAN.

(https://de.mathworks.com/help/deeplearning/examples/train-generative-adversarial-network.html)

In this example, there is a line which "classifies" the generated outputs with the help of the discriminator network:

dlYPredGenerated = forward(dlnetDiscriminator, dlXGenerated); 

I expected the output to consist of 2 labels: "Original" or "Fake". Instead, i get a long list of numbers:

(:,:,1,1) =
    5.9427
(:,:,1,2) =
    7.5930
(:,:,1,3) =
    9.3393
etc.

How can i use the resulting discriminator after training a GAN with a set of images? I just want to have a 2 - label classification, consisting of "original" and "fake".