Anomaly detection tasks in real-world settings are typically complex and variable, and various types of defects can occur in different products. Therefore, the datasets we construct are required to cover multiple scenarios and defect types of anomaly detection. We initially acquired and sampled from nine publicly available IAD datasets. To further expand the scenarios, we also manually gathered data from four scenarios applicable to IAD tasks to form several independent datasets and eliminated… See the full description on the dataset page:
https://huggingface.co/datasets/zhaolutuan/AnomalyCoT.
