CASIA-LMC-Lab/AnomalyGPT

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1133 stars · 144 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

AnomalyGPT is the first Large Vision-Language Model based method for industrial anomaly detection, identifying the presence and location of anomalies in images without manual threshold tuning. It combines a pre-trained image encoder with an LLM (Vicuna) and supports multi-turn dialogue and few-shot in-context learning.

Use cases

• detect defects in industrial product images
• find anomalies in manufacturing inspection photos without setting thresholds
• localize defective regions in images using a vision-language model
• few-shot anomaly detection with one normal sample
• chat about images to identify what is abnormal
• train a custom anomaly detection model on my own dataset

When to choose

• you need image-level and pixel-level anomaly detection with natural-language explanations
• you want to avoid manually tuning anomaly score thresholds
• you have GPU resources and want few-shot industrial defect detection
• you want a research-grade LVLM baseline for anomaly detection on MVTec-AD style data

When to avoid

• you need a production-ready commercial solution - the code is CC BY-NC-SA licensed for non-commercial use only
• you lack GPU hardware to run ImageBind and Vicuna checkpoints
• you need real-time high-throughput inspection on edge devices
• you need general-purpose object detection rather than anomaly detection

Facets

library · maturity maintenance

machine-learning computer-vision image-processing llm-inference deep-learning computer-vision image-processing large-language-models artificial-intelligence python anomaly-detection vision-language-model industrial-inspection multimodal few-shot-learning research-code aaai-2024 manufacturing gpu linux

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