MIXED PCB DEFECT DATASET

This dataset contains images focusing on printed circuit boards (PCBs) and their defects. To maintain uniformity, the images are resized to a standard 640 x 640 pixels. To increase the dataset's realism and relevance for real-time sensor applications, intentional augmentation was applied, adding extra defects to simulate real-world scenarios in PCB manufacturing. Various augmentation techniques were used to diversify the dataset, ensuring better algorithm performance during training and evaluation. The dataset features annotations that precisely label the induced defects, such as missing holes, mouse bites, open circuits, shorts, spurs, and spurious copper issues. With its precise annotations and intentional augmentation, this dataset is a valuable resource for advancing research in real-time PCB defect detection and classification.本数据集包含以印刷电路板（printed circuit boards，PCBs）及其缺陷为主题的图像。为保证图像规格统一，所有图像均被调整至640×640像素的标准尺寸。为提升数据集的真实性及其在实时传感器应用中的适配性，本数据集采用了人为数据增强手段，通过添加额外缺陷以模拟PCB制造过程中的真实工业场景。本数据集运用多种数据增强技术丰富样本多样性，确保算法在训练与评估阶段可获得更优异的性能表现。数据集附带精准标注的人工引入缺陷，涵盖漏孔、鼠咬缺陷、开路、短路、毛刺以及多余铜箔等典型PCB缺陷类型。凭借精准的缺陷标注与人为数据增强手段，本数据集可为实时PCB缺陷检测与分类领域的研究进阶提供极具价值的支撑资源。