Fine-grained　ship　image　recognition　is　to　discriminate　different　subcategories　of　ship　categories.　Because　of　the　lack　of　ship　data　sets　and　the　particularity　of　the　identification　task,　fine-grained　ship　recognition　is　a　challenging　task.　We　designed　a　part　assignment　module,　which　has　the　function　of　part　assignment　and　extracting　import　part　information.　Then,　we　added　the　module　to　the　SimCLR　contrastive　learning　framework.　This　method　uses　the　module　to　assignment　the　information　in　the　feature　map,　extract　the　key　information　of　key　regions,　increase　the　learning　ability　of　contrast　learning　for　key　information,　in　the　end,　the　accuracy　of　fine-grained　classification　can　be　improved.　©　2023　IEEE.