blaz-r/SuperSimpleNet
Official implementation of SuperSimpleNet [ICPR 2024, JIMS 2025]
This project helps quality control and manufacturing professionals quickly and reliably find flaws on product surfaces. It takes images of products, then identifies and highlights any defects present. This is designed for quality assurance engineers, production managers, and technicians who need to automate visual inspection.
154 stars.
Use this if you need to detect surface defects on manufactured goods using either unlabeled (unsupervised) or labeled (supervised) image data.
Not ideal if you are looking to analyze complex internal structures or perform tasks unrelated to surface defect identification.
Stars
154
Forks
25
Language
Python
License
MIT
Category
Last pushed
Oct 16, 2025
Commits (30d)
0
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