This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.

A collection of public datasets for surface metal defects detection task. Source, and roboflow (ready to use) links are included.

The first to adopt the YOLOF model on a metal defect NEU-DET dataset. Using several image preprocessing methods, including Edge Detection, Denoising, Sharpening, and SR, were experimented on the metal defect NEU-DET dataset. In the proposed optimized batch size, backbone, soft efficient non-maximum sup-pression (Soft-NMS), and threshold of YOLO.