Research on the impact of marking methods for deformation defects of drainage pipes on intelligent recognition algorithms
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1.School of Civil and Hydraulic Engineering, Hefei University of Technology,Hefei 230009, China; 2.Shanghai Survey and Design Institute Co., Ltd.,Shanghai 200335, China

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TU992.4;TN.9

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    Abstract:

    In view of the lack of annotation standards in the current drainage pipe defect dataset, taking the pipe deformation defect as the research object, the YOLOv8 detection model was used to study the influence of different annotation methods on the pipe defect recognition results. Firstly, the defect images were classified into two major categories based on the characteristics of the deformation defects: Convex block deformation and overall deformation. For the convex block deformation, two labeling methods, namely convex block full marking and convex block half marking, were adopted. For the overall deformation, both overall full marking and overall half marking were used for labeling. Five independent tests were conducted for each labeling method. The results show that for the convex block deformation using the full labeling method of convex blocks, the values of the four evaluation indicators P, R, F1 and mAP50 are 76.56%, 74.36%, 75.43% and 72.12% respectively. The four values of the semi-labeled convex block annotation method are 88.51%, 76.77%, 82.17% and 83.14%, respectively. Therefore, the semi-labeled convex block annotation method is more suitable for convex block deformation. For the overall deformation, when the overall full labeling method was adopted, the values of the four evaluation indicators P, R, F1 and mAP50 were 83.85%,84.92%,84.34% and 84.46%, respectively. However, when the overall semi-labeling method was used for three training sessions, it was found that none of the four evaluation indicators could tend to stabilize. It indicates that the overall full-label annotation method is more suitable for overall deformation.

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  • Received:
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  • Online: June 08,2026
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