Xiaohao-Xu/Customizable-VLM
[CSCWD 2025, Best Student Paper] Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning
This project helps quality control engineers and manufacturing line managers automatically spot defects in products using visual and textual descriptions. You provide images of items, along with any relevant contextual information or historical data, and it identifies unusual patterns or anomalies, flagging potential defects or errors. It's designed for professionals overseeing production lines or performing detailed product inspections.
No commits in the last 6 months.
Use this if you need to automate the detection of unusual or faulty items on a production line using both visual inspection and descriptive text.
Not ideal if you're looking for a simple, out-of-the-box solution without any programming or API key setup.
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29
Forks
1
Language
Python
License
MIT
Category
Last pushed
May 24, 2025
Commits (30d)
0
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