The NEU-CLS dataset is collected from real industrial production lines. It is publicly released by the Surface Inspection Laboratory of Northeastern University, constructed explicitly for strip surface defect classification. This dataset covers six common types of strip surface defects: Crazing, Scratch, Pitted Surface, Patch, Rolled-in Scale, and Inclusion. The image's defect morphologies are diverse, presenting high complexity and diversity, effectively simulating the challenges of defect detection in practical application scenarios. Each defect category contains 300 images, all of which are grayscale with a resolution of 200×200 pixels.