Due to the diversity of human body types,the garments are usually unfit during the trying on process.In order to assist the pattern makers to find and solve the pattern problems,this paper took women's pants as an example,summarized common images of women's trouser malpractices as datasets,including obvious front crotch excess,obvious cat whiskers in the front crotch,pinched crotch in the back piece,and obvious diagonal folds in the thigh-root in the back piece,and conducted experiments using the YOLOv8 model in deep learning algorithms.In the model testing stage,the accuracy,recall rate,and(-P)A(Iou=50％)all reached over 98％.At the same time,the rationality of the defect correction sugges-tions was verified through defect correction experiments.The study achieved intelligent detection and correction of defects in women's trousers.
关键词
深度学习/目标检测/板型弊病/纸样修正/YOLOv8模型
Key words
deep learning/target detection/paper pattern defects/paper pattern correction/YOLOv8 model
维普
万方数据