Anomaly score unclear

[JoaoMBarbosa99]

I've been using the GANomaly model on a custom dataset (sixray) and I'm having a hard time trying to analyse results through visualization.

As far as I understood, there are two options to set output scores.

Without normalization The model may predict scores bigger than 1 without normalization min_max. However I get always "abnormal" labels on my results. Probably because all of the images (normal and abnormal) are bigger that the adaptive threshold. Something that doens't make sense to me.

With normalization If I use normalization "min_max" the threshold becomes automatically 0.5 and the "adaptive_threshold" doens't do anything anymore. With this method I am getting F1 Score = 0 and all of the output images display "abnormal" labels. The "normal" have in fact lower scores (near 50%) but are stil above 0.5.

Ideally I would like to see in the image a result between 0 ad 1 (0% and 100%) but with an adaptive threshold as well. If the image was considered nomral it would appear "Normal: 'score lower than threshold'. If the image was in fact considered anomalous it would appear "Anomalous": 'score lower than threshold'.

In the article "GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training" on image 6a, the results are between 0 and 1 and the threshold is not 0.5.