yolov8添加EffectiveSE 注意力模块

###################### BiFPN  ###################################

# BiFPN
# 两个特征图add操作
class BiFPN_Add2(nn.Module):
    def __init__(self, c1, c2):
        super(BiFPN_Add2, self).__init__()
        self.w = nn.Parameter(torch.ones(2, dtype=torch.float32), requires_grad=True)
        self.epsilon = 0.0001
        self.conv = nn.Conv2d(c1, c2, kernel_size=1, stride=1, padding=0)
        self.silu = nn.SiLU()

    def forward(self, x):
        w = self.w
        weight = w / (torch.sum(w, dim=0) + self.epsilon)
        return self.conv(self.silu(weight[0] * x[0] + weight[1] * x[1]))


# 三个特征图add操作
class BiFPN_Add3(nn.Module):
    def __init__(self, c1, c2):
        super(BiFPN_Add3, self).__init__()
        self.w = nn.Parameter(torch.ones(3, dtype=torch.float32), requires_grad=True)
        self.epsilon = 0.0001
        self.conv = nn.Conv2d(c1, c2, kernel_size=1, stride=1, padding=0)
        self.silu = nn.SiLU()

    def forward(self, x):
        w = self.w
        weight = w / (torch.sum(w, dim=0) + self.epsilon)
        return self.conv(self.silu(weight[0] * x[0] + weight[1] * x[1] + weight[2] * x[2]))


###################### BiFPN  ###################################

1.在ultralytics/nn/modules/block.py文件的最后加入上述代码。并在文件上方的__all__中加入下述标框代码

2.在ultralytics/nn/modules/__init__.py中加入下述标框代码

3.ultralytics/nn/tasks.py中加入下述标框代码

4.在ultralytics/cfg/models/v8目录下创建yolov8-BiFPN.yaml文件，复制下述代码。

# Ultralytics YOLO 

标签：__,Conv,nn,self,yolov8,EffectiveSE,模块,BiFPN,C2f	

From： https://blog.csdn.net/qq_63632802/article/details/137077456