MPDD

Metal Parts Defect Detection Dataset

Introduced 2021-12-13

MPDD is a dataset aimed at benchmarking visual defect detection methods in industrial metal parts manufacturing. It consists of more than 1000 images with pixel-precise defect annotation masks. The dataset is divided into the training subset with anomaly-free samples and the validation subset that contains both normal and anomalous samples. The dataset can be downloaded at the following link.

Benchmarks

Anomaly Detection/Detection AUROC Anomaly Detection/Segmentation AUROC Anomaly Detection/Segmentation AUPRO