yolo v8 model.export

YOLOv8模型提供了export模式，用于将模型导出为可用于部署的格式。在这种模式下，可以将模型转换为其他软件应用程序或硬件设备可以使用的格式。如果需要将YOLOv8模型转换为OpenVINO IR模型格式，可以使用model.export函数，并指定format参数为"openvino"。此外，还可以选择保留动态输入的选项，通过将dynamic参数设置为True来实现。以下代码展示了将YOLOv8模型导出为OpenVINO IR模型格式的示例:

from pathlib import Path

model_path = Path(f"{MODEL_NAME}_openvino_model/{MODEL_NAME}.xml")
if not model_path.exists():
    model.export(format="openvino", dynamic=True, half=False)

这段代码将模型导出为OpenVINO IR格式，并将结果保存在`{MODEL_NAME}_openvino_model/{MODEL_NAME}.xml`路径下，可以根据实际情况自行调整路径。<em>1</em><em>2</em><em>3</em>
#### 引用[.reference_title]
- *1* [【目标检测】YOLOV8实战入门（六）模型导出](https://blog.csdn.net/qq_43456016/article/details/130448606)[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^v92^chatsearchT0_1"}} ] [.reference_item]
- *2* [优化+量化，让你的YOLOv8获得1000+ FPS性能](https://blog.csdn.net/m0_59448707/article/details/129616678)[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^v92^chatsearchT0_1"}} ] [.reference_item]
- *3* [Yolov8教程，安装，训练，推理速度太强悍了，详细教学](https://blog.csdn.net/m0_62479378/article/details/130472736)[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^v92^chatsearchT0_1"}} ] [.reference_item]
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