A multi-task structured network was designed for the cold metal transfer weld (CMT) weld droplet contour feature by combining the target detection and image segmentation algorithms,which could monitor the weld droplet position orientation and extract the accurate outer contour to realize the datamation of image information for the CMT weld droplet transition process,thus reflecting the weld droplet behavior of the CMT wire feeding process.The original images taken by the high-speed camera were input directly into the network,and the positioning of the weld droplet was realized by using R-Net with an accuracy of 97.31% and a preliminary mask was generated directly on this basis.The preliminary mask was refined by the main part of the multi-task structured network and combined with the preliminary segmented foreground map,the weld droplet contour could be extracted,with a fitting accuracy of 988%.In addition,using the above-designed network,the change of weld droplet morphology during the complete welding cycle of CMT can be obtained to visualize and datamation the CMT weld droplet transition process.