yolov8获得掩膜

根据引用和[2]的信息，YOLOv8模型通过矩阵乘法将output0的后32个字段与output1的数据相乘，从而得到对应目标的掩膜数据。具体而言，output0的后32个字段用于计算掩膜数据，而output1则提供了计算掩膜数据所需的关键信息。因此，通过对输出节点output0和output1的处理，YOLOv8模型能够获得目标的掩膜数据。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [用OpenVINO C++ API编写YOLOv8-Seg实例分割模型推理程序](https://blog.csdn.net/gc5r8w07u/article/details/131303130)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
- *2* *3* [【YOLOv8-seg】实战一：手把手教你使用YOLOv8实现实例分割](https://blog.csdn.net/virobotics/article/details/131329792)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
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