ADNet is a large-scale, multi-domain benchmark for visual anomaly detection and localization. It contains 196,294 RGB images from 380 real-world categories across five application domains: Electronics, Industry, Agrifood, Infrastructure, and Medical.
ADNet standardizes data collected from 49 publicly available anomaly-detection datasets into a unified MVTec-style structure. The benchmark supports normal-only training, image-level anomaly detection, pixel-level anomaly… See the full description on the dataset page:
https://huggingface.co/datasets/linglingling009/ADNet.
