Updated
- Change the way anomaly scores are normalized by default, instead of using a [0-1] range with a 0.5 threshold, the scores are now normalized to a [0-1000] range with a threshold of 100, the new score represents the distance from the selected threshold, for example, a score of 200 means that the anomaly score is 100% of the threshold above the threshold itself, a score of 50 means that the anomaly score is 50% of the threshold below.
- Change the default normalization config name for anomaly from `min_max_normalization` to `score_normalization`.
Fixed
- Fix the output heatmaps and preditions of anomaly inference tasks not being saved properly when images belonged to
different classes but had the same name.