# VisA benchmark
VisA provides normal and anomalous product images with anomaly segmentation masks. PCB1, capsules and cashew are included. The official one-class split fits on normal images; labelled normal and anomalous images are used for evaluation. Multiclass masks can be reduced to binary anomaly masks. Normal images have no stored anomaly mask. Image-level labels establish benchmark anomaly status, not a validated diagnosis for a newly uploaded photograph.

# Scope and attribution
The VisA dataset is released by Amazon Science under CC BY 4.0. Attribute Yang Zou, Jongheon Jeong, Latha Pemula, Dongqing Zhang and Onkar Dabeer, SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation, ECCV 2022. DefectRAG sample previews are resized JPEG derivatives. Dataset annotations are benchmark evidence, not factory acceptance tolerances.