Filters

A dataset of filter surface defectsOil filters are a crucial component of an automobile's engine system. Defect detection plays a vital role in ensuring quality control during the filter production process. Traditional detection methods fail to meet the efficiency and quality standards required for modern industrial production. The characteristics of few-shot learning and the small size of filter defects hinder the effective training and detection capabilities of deep learning models. Therefore, we proposes a dataset generation method based on StyleGAN3.