YOLOv12全栈开发手册：从算法研发到商业落地的完整技术闭环

YOLOv12全栈开发手册：从算法研发到商业落地的完整技术闭环

---

第一章：算法研发与模型设计

提示语：突破性创新！YOLOv12混合维度注意力机制详解

1.1 跨维度注意力模块实现

class HybridAttention(nn.Module):
    def __init__(self, channels):
        super().__init__()
        self.channel_att = nn.Sequential(
            nn.AdaptiveAvgPool2d(1),
            nn.Conv2d(channels, channels//8, 1),
            nn.ReLU(),
            nn.Conv2d(channels//8, channels, 1),
            nn.Sigmoid()
        )
        self.spatial_att = nn.Sequential(
            nn.Conv2d(2, 1, 7, padding=3),
            nn.Sigmoid()
        )

    def forward(self, x):
        ca = self.channel_att(x)
        sa_input = torch.cat([x.mean(dim=1, keepdim=True), 
                           x.max(dim=1, keepdim=True)[0]], dim=1)
        sa = self.spatial_at