LucStrater/GeneralAD
GeneralAD
This project helps quality control inspectors and manufacturing engineers automatically spot defects or unusual items in images. You provide a set of 'normal' product images, and it learns to identify anomalies—from subtle imperfections to entirely incorrect parts. The output is a score indicating how anomalous an image is, along with visual maps highlighting where the anomalies are located.
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Use this if you need to reliably detect manufacturing defects, identify out-of-spec products, or find unusual objects in large batches of images across various industrial or semantic contexts.
Not ideal if your anomaly detection task doesn't involve image data or if you need to detect anomalies based purely on numerical or categorical data without visual components.
Stars
56
Forks
5
Language
Python
License
MIT
Category
Last pushed
Dec 17, 2024
Commits (30d)
0
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