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xrli-U / MuSc

This is an official PyTorch implementation for "MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images" (MuSc ICLR2024).
MIT License
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can this method applied on other datasets? #12

Open leolle520 opened 1 month ago

leolle520 commented 1 month ago

How to apply this method on my custom dataset and do the prediction please? I don't see any training process, it's amazing.

Thank you.

xrli-U commented 1 month ago

Our method uses a pre-trained image encoder of CLIP as the feature extractor, requiring no additional training and fine-tuning. In other words, most current feature extractors can be used in our method. All the feature extractors used in the script can be downloaded from the following link, CLIP: https://github.com/mlfoundations/open_clip DINO: https://github.com/facebookresearch/dino DINO_v2: https://github.com/facebookresearch/dinov2

xrli-U commented 1 month ago

If you want to test on your custom dataset, you can write an interface with the same output directly from def getitem(self, idx) in ./datasets/mvtec.py