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guojiajeremy/Dinomaly ★ 526 64 DATA_RESEARCH

This repository implements Dinomaly, a reconstruction-based unsupervised anomaly detection method for industrial inspection datasets. It uses vision transformers (primarily DINOv2) as feature extractors with a noisy bottleneck and linear attention mechanism. The code supports both class-separated and unified training across MVTec-AD, VisA, and Real-IAD datasets. Key components include dataset loaders, custom optimizers, training utilities, and evaluation metrics. While the research code achieves state-of-the-art results, it contains hardcoded paths, version-specific dependencies, and dataset-specific logic that limit immediate reproducibility.

RATING: 7.0/10 REPRO: 5.0/10 MAINT: active DRIFT: medium
#anomaly-detection #unsupervised-learning #vision-transformer #industrial-inspection #reconstruction-based #pytorch #feature-extraction
▸ 3 reusable components found
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