Taktpixel2025PD-CD: Taktpixel 2025 Printing Defect Change Detection Dataset

Taktpixel2025PD-CD is a dataset for evaluating change detection models in the domain of industrial printing inspection. It contains image pairs of printed materials scanned from both offset and inkjet print samples. Each image pair includes: A master image (reference, assumed defect-free) A target image (possibly containing a defect) A pixel-wise binary mask representing the defect region The dataset is divided into train, val, and test splits, and organized into the standard A/, B/, and OUT/ folder structure commonly used in change detection tasks. Six common defect types are labeled: Black spot Color shift Friction Hair Line Pinhole Candidate defect regions were extracted using comparative image inspection techniques and manually validated through expert review. Ground-truth masks are refined to exclude false positives caused by normal printing variation. This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. It is suitable for training and benchmarking machine learning models, particularly for applications in visual inspection and quality assurance in the printing industry.Taktpixel2025PD-CD 是一款面向工业印刷检测领域的变化检测模型评测数据集。该数据集包含源自胶印与喷墨印刷样本的印刷品扫描图像对，每一组图像对均包含以下三部分： 1. 基准参考图像（预设无印刷缺陷） 2. 待检目标图像（可能存在印刷缺陷） 3. 用于标记缺陷区域的像素级二值掩码 该数据集划分为训练集、验证集与测试集，并采用变化检测任务中通用的标准A/、B/与OUT/文件夹组织结构。 数据集共标注了六种常见印刷缺陷类型：黑点、色偏、摩擦痕、发丝缺陷、线条缺陷与针孔缺陷。 候选缺陷区域通过对比图像检测技术提取，并经领域专家审核完成人工校验；真值掩码经过精细化优化，以排除由正常印刷波动引发的假阳性样本。 本数据集采用知识共享署名-相同方式共享4.0国际（Creative Commons Attribution-ShareAlike 4.0 International，CC BY-SA 4.0）许可协议发布，适用于机器学习模型的训练与基准测试，尤其适配印刷行业的视觉检测与质量保障相关应用场景。