acnet放在yolov5中，代码实现

将 Acnet 网络放在 YOLOv5 中需要进行以下步骤：

1.在 `models/yolo.py` 文件中导入 Acnet 模块：

from models.common import Conv, BottleneckCSP, ACBlock

2.在 `models/yolo.py` 文件中修改 `CSPDarknet` 类的定义，将原先的卷积层替换为 ACBlock：

class CSPDarknet(nn.Module):
    def __init__(self, layers, in_channels=3, stem_channels=32, out_channels=256):
        super(CSPDarknet, self).__init__()
        self.stem = nn.Sequential(
            Conv(in_channels, stem_channels, kernel_size=3, stride=1, padding=1, bias=False),
            ACBlock(stem_channels, stem_channels*2, 3, 2, 1),
            BottleneckCSP(stem_channels*2, stem_channels*2, n=1)
        )
        ...

    def forward(self, x):
        x = self.stem(x)
        ...

3.在 `models/yolo.py` 文件中修改 `YoloV5` 类的定义，将原先的卷积层替换为 ACBlock：

class YoloV5(nn.Module):
    def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None):
        super(YoloV5, self).__init__()
        ...
        self.backbone = nn.Sequential(
            ...
            ACBlock(512, 1024, 3, 2, 1),
            BottleneckCSP(1024, 1024, n=3, shortcut=False),
            ACBlock(1024, 512, 3, 2, 1),
            ...
        )
        ...

    def forward(self, x):
        ...
        x = self.backbone(x)
        ...

这样就可以将 Acnet 网络放在 YOLOv5 中进行训练了。