An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
The normalization metrics are resetted before every validation. Is there any flaw in this logic or does it makes sense, so that models that have very different anomaly map and pred score magnitudes during training epochs are optimally normalized.
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📝 Description
Fixes: https://github.com/openvinotoolkit/anomalib/discussions/2122#discussioncomment-9740488 and https://github.com/openvinotoolkit/anomalib/issues/2027 and https://github.com/openvinotoolkit/anomalib/issues/2139#issue-2352819822
The normalization metrics are resetted before every validation. Is there any flaw in this logic or does it makes sense, so that models that have very different anomaly map and pred score magnitudes during training epochs are optimally normalized.
✨ Changes
Select what type of change your PR is:
✅ Checklist
Before you submit your pull request, please make sure you have completed the following steps:
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