yolov8预训练权重

回答: YOLOv8的预训练权重是通过加载.pt文件进行的。在运行改进模型时，可以选择载入预训练权重进行迁移学习，具体操作如下：
1. 打开yolov8->ultralytics->yolo->engine->model.py文件
2. 在def _new函数中插入以下代码来加载预训练权重：

ckpt = torch.load('yolov8n.pt')
csd = ckpt['model'].float().state_dict()
csd = intersect_dicts(csd, self.model.state_dict())
self.model.load_state_dict(csd, strict=False)
print(f'Transferred {len(csd)}/{len(self.model.state_dict())} items')

插入的具体位置请参考上面提到的图示。这样就可以载入预训练权重进行迁移学习了。<em>1</em><em>2</em><em>3</em>
#### 引用[.reference_title]
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