用一键扩散模型把考古陶器草图自动转为出版级墨线图。
PyPotteryInk: One-Step Diffusion Model for Sketch to Publication-ready Archaeological Drawings
- 基于改进的img2img-turbo架构,单步完成草图到成图转换。
- 在意大利史前陶器数据集上还原出纹饰与器型等关键细节。
- 专家评估达标出版标准,处理速度从小时级降至秒级。
考古陶器记录传统上依赖耗时的手工流程,将铅笔草图转化为出版级墨线图。本文提出PyPotteryInk,一个开源自动化流程,利用单步扩散模型实现该转换。系统基于修改版img2img-turbo架构,在单次前向传播中处理草图,同时保留关键形态特征,并符合考古记录标准与分析价值。采用高效的分块动态重叠策略,可生成任意尺寸的高分辨率输出。在意大利史前陶器数据集上的实验表明,模型能准确捕捉细纹、器型轮廓及把手等结构元素。专家评估确认生成图达到出版标准,单图处理时间由数小时缩短至数秒。模型仅需少量微调即可适应不同考古语境,具备跨风格适用性。预训练模型、Python库及完整文档均已公开,便于学界应用。
原文摘要 · Abstract (English)
Archaeological pottery documentation traditionally requires a time-consuming manual process of converting pencil sketches into publication-ready inked drawings. I present PyPotteryInk, an open-source automated pipeline that transforms archaeological pottery sketches into standardised publication-ready drawings using a one-step diffusion model. Built on a modified img2img-turbo architecture, the system processes drawings in a single forward pass while preserving crucial morphological details and maintaining archaeologic documentation standards and analytical value. The model employs an efficient patch-based approach with dynamic overlap, enabling high-resolution output regardless of input drawing size. I demonstrate the effectiveness of the approach on a dataset of Italian protohistoric pottery drawings, where it successfully captures both fine details like decorative patterns and structural elements like vessel profiles or handling elements. Expert evaluation confirms that the generated drawings meet publication standards while significantly reducing processing time from hours to seconds per drawing. The model can be fine-tuned to adapt to different archaeological contexts with minimal training data, making it versatile across various pottery documentation styles. The pre-trained models, the Python library and comprehensive documentation are provided to facilitate adoption within the archaeological research community.
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