LuigiFederico/PatchCore-for-Industrial-Anomaly-Detection
PatchCore method for Industrial Anomaly Detection + CLIP
This project helps quality control and operations engineers in manufacturing identify defective parts on production lines. It takes images of normally functioning parts as input during training and then, when presented with new parts, outputs whether a part is defective and highlights the specific area of the defect. This is particularly useful for visual inspection tasks where only examples of 'good' products are readily available.
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Use this if you need to automate defect detection in industrial manufacturing when you primarily have access to images of non-defective items for training.
Not ideal if you need a solution for anomaly detection in non-image data or if you have a balanced dataset of both defective and non-defective parts for training.
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Language
Python
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Last pushed
Aug 28, 2024
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