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blaz-r avatar blaz-r commented on August 21, 2024 1

Hello, that is correct. All models in currently Anomalib are unsupervised, using only good data for training. Labeled anomalous images are only used in test phase, where you require ground truth annotation to tell how good the model is performing.

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blaz-r avatar blaz-r commented on August 21, 2024

Hello. You can still train without the labels, but you won't be able to test the model.

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korkard avatar korkard commented on August 21, 2024

Thanks for your reply.
Are you saying that I can train in a state where normal and abnormal are mixed?
I think good, bad is labels.

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blaz-r avatar blaz-r commented on August 21, 2024

Sorry I understood the question incorrectly. All models implemented in Anomalib only utilize normal data for training, so you should be able to train the model using your good data, which does not require labels. The abnormal data can be used as part of the test set and shouldn't be mixed with good data.

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aradwan777 avatar aradwan777 commented on August 21, 2024

hi to clarify, all models that exist in anomalib are unsupervised? Or in this case semi-supervised, I am not sure, but the learning is only done on the good images, that is the only data required, correct? Thank you, as I was confused if these were supervised(requiring masks for training, thus labeling for custom data) or not

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Abhijeet241093 avatar Abhijeet241093 commented on August 21, 2024

Is it possible, to test operation without using ground truth ?

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Sj-Yuan avatar Sj-Yuan commented on August 21, 2024

If you just need the result of anomaly detection but not localizaition, the ground truth is not required, you can just prepare some black image as the fake ground truth for test phase.

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