yolov8有特征金字塔结构吗

根据提供的引用内容，可以得知YOLOv8中有特征金字塔结构。在YOLOv8中，SPPF模块是一个常见的特征金字塔模块，可以通过修改SPPF模块来改进YOLOv8模型。此外，YOLOv8还引入了全局信息注意力机制并改进了特征提取网络和特征金字塔结构，以提高模型对小目标特征的提取和检测能力。同时，YOLOv8还使用了自适应锚来提高模型的检测精度。

下面是YOLOv8中特征金字塔结构的示例代码：

import torch.nn as nn

class SPPF(nn.Module):
    def __init__(self, in_channels, out_channels):
        super(SPPF, self).__init__()
        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=1)
        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, padding=1)
        self.conv3 = nn.Conv2d(out_channels, out_channels, kernel_size=3, padding=1)
        self.conv4 = nn.Conv2d(out_channels, out_channels, kernel_size=3, padding=1)
        self.maxpool1 = nn.MaxPool2d(kernel_size=5, stride=1, padding=2)
        self.maxpool2 = nn.MaxPool2d(kernel_size=9, stride=1, padding=4)
        self.maxpool3 = nn.MaxPool2d(kernel_size=13, stride=1, padding=6)
    def forward(self, x):
        x = self.conv1(x)
        x = self.conv2(x)
        x = self.maxpool1(x)
        x = self.conv3(x)
        x = self.maxpool2(x)
        x = self.conv4(x)
        x = self.maxpool3(x)
        return x