基于Y0L0v5的旋轉(zhuǎn)邊界框電容器目標(biāo)檢測(cè)

Object Detection of Rotated Bounding Boxes for Capacitors Detection Based on YOLOv5

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中圖分類(lèi)號(hào)：TP391.4 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：2096-4706（2025）11-0033-05

Object Detection of Rotated Bounding Boxes for Capacitors Detection Based on YOLOv5

ZHANG Zhihao1, YANG Xuejun1, SHEN Mouquan', HU Jiwei2, KE Yun2, LI Chaochao2 (1.CollegeofElectricalEngineeringandControlScience,NanjingTech University,Nanjing211816,China; 2.ChangxingHuaqiangElectronicsCo.,Ltd.,Huzhou 313119, China;)

Abstract:To solve the problem that classicalYOLOv5object detection algorithm can only achieve object localization with horizontalrectangular bounding boxes,thispaper designsanobjectdetection methodof rotated bounding boxes for capacitors based on the YOLOv5s model.This method transforms the angle prediction problem from aregresion problem to aclassificationproblem by using circular smooth labels,and describes the lossfunction ofangle prediction using binary cross-entropyloss.Additionally,theorginal traningdataisexpandedtroughreplication,rotationtransformation,and stitchingtoimprovetheaccuracyand generalizationabilityofthemodel.Experimentalresultsonarealcapacitorsdataset showthat the improved object detection algorithm ofrotated bounding boxes forcapacitors achieves an average accuracy of 83.5% .Compared withthe original YOLOv5 model,the predicted object bounding boxes are more consistent with the actual rectangular contours of the capacitors.

Keywords: Object Detection; rotated bounding box;Deep Learning; capacitor

0 引言

在環(huán)境污染和石油危機(jī)雙重壓力下，能源結(jié)構(gòu)轉(zhuǎn)型和清潔可再生能源發(fā)電技術(shù)成為能源發(fā)展的重要方向，電能存儲(chǔ)逐漸成為智能電網(wǎng)和構(gòu)建能源互聯(lián)網(wǎng)的關(guān)鍵技術(shù)[1]，電容器的地位日益突出。（剩余10598字）