Ceramic-defect: Annotated dataset for surface defect detection on ceramic substrates in manufacturing

The image pixel range covers from 1024×1024 to 4096×4000 pixels, fully preserving the overall layout and subtle defect characteristics. The dataset contains a total of 7,360 defect instances, all visible defects are annotated with precise bounding boxes, and the annotation files follow the COCO JSON format. Conversion versions in PASCAL VOC and YOLO formats are also provided to ensure compatibility with mainstream object detection frameworks (e.g., YOLOv8, YOLOv11, Faster R-CNN, etc.).

This dataset is designed to provide researchers in the fields of computer vision, Automated Optical Inspection (AOI), and semiconductor quality control with standardized, highly reusable benchmark resources, driving the development of ceramic substrate defect detection algorithms toward high precision and high robustness, thereby offering data support for the intelligent upgrade of the semiconductor manufacturing industry.