建筑图纸到钢筋下料单的智能生成技术OA

This paper proposes a deep learning-based method for intelligent generation of cutting lists from architectural drawings.The approach integrates object detection and Transformer networks to achieve accurate table region localization and efficient information classification.Experiments were conducted on a dataset of 200 architectural drawings,which was divided into training,validation,and test sets in a ratio of 7∶2∶1.The results show that the proposed system achieves a table data extraction accuracy of 99.8%.In practical applications,it reduces cutting list preparation time by 99.0%and lowers the material waste rate to 7.43%,offering an effective technical solution for intelligent construction management.