sdls anomaly detect

A dataset for process anomaly detection in scientific experiments. The dataset is collected from a fully automated PDMS synthesis workflow involving collaborative robots. Images were captured from first-person views using end-effector cameras mounted on mobile and fixed robotic arms. In total, the dataset includes 1,671 images and 2,788 image-text pairs. Each sample contains step-specific descriptions, anomaly labels, and region-level annotations. This dataset supports a range of visual anomaly detection tasks, including image-text classification, anomaly type recognition, anomaly localization, grounded captioning, and anomaly attribution analysis.