I use different image classification models, CNN, VGG, and DenseNet, to find images with steel defects, and find out DenseNet gives a better result. I use UNet to do image segmentation and predict the type of defects. I also use the Albumentations library to do data augmentation. Please refer to my GitHub: https://github.com/tsunghanwu0323/steel-defect-detection