发表机构
Sapienza Università di Roma; Parco Archeologico del Colosseo; Georg-August-Universität Göttingen; ISMed-CNR – Istituto di Studi sul Mediterraneo（罗马大学; 罗马斗兽场考古公园; 哥廷根大学; 意大利国家研究委员会地中海研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出PyPottery，一个开源AI驱动套件，通过四个集成模块半自动化陶器记录流水线，在50张图纸上实现40倍中位感知加速，展示了AI辅助考古记录的潜力。
AI 中文摘要
陶瓷材料的研究是考古研究的基石，然而陶器记录的后处理工作流程仍然劳动密集，并造成显著的发表瓶颈。本文介绍了PyPottery，一个开源的、AI驱动的套件，旨在半自动化完成整个陶瓷记录流水线。该套件包含四个集成模块：PyPotteryScan用于自动图像提取和手写识别；PyPotteryInk用于铅笔绘图的自动上墨；PyPotteryTrace用于语义感知的矢量化；以及PyPotteryLayout用于自动布局生成。在来自意大利Terramara di Montale的50张手绘图纸（包含240幅陶器绘图）上进行的评估中，该框架实现了显著的时间节省，可用性研究参与者证实了这一点，他们报告的中位感知加速比为传统工作流程的40倍（范围：17.5倍至120倍）。这些结果凸显了AI辅助工具在考古记录中的潜力，同时本文探讨了将认知劳动战略性重新分配为增强而非自动化的方向。
英文摘要
The study of ceramic materials constitutes a cornerstone of archaeological research, yet the post-production workflow for pottery documentation remains labor-intensive and creates significant publication bottlenecks. This paper presents PyPottery, an open-source, AI-powered suite designed to semi-automate the complete ceramic documentation pipeline. The suite comprises four integrated modules: PyPotteryScan for automated image extraction and handwriting recognition; PyPotteryInk for automatic inking of pencil drawings; PyPotteryTrace for semantically-aware vectorization; and PyPotteryLayout for automated layout generation. Evaluated on 50 hand-drawn sheets containing 240 pottery drawings from the Terramara di Montale (Italy), the framework achieved substantial time savings confirmed by usability study participants, who reported a median perceived speedup of 40$\times$ over traditional workflows (range: 17.5$\times$--120$\times$). These results highlight the potential of AI-assisted tools in archaeological documentation, while the paper addresses the strategic redistribution of cognitive labor toward augmentation rather than automation.
