mobileone替换yolov5的backbone的代码
时间: 2023-09-21 12:03:37 浏览: 138
这是一个示例代码,用MobileNetV3替换YoloV5的backbone:
```
import torch
import torch.nn as nn
import torchvision.models as models
from yolov5.models.yolo import Detect
class YoloV5MobileNet(nn.Module):
def __init__(self, num_classes=80):
super(YoloV5MobileNet, self).__init__()
self.backbone = models.mobilenet_v3_small(pretrained=True).features[:-1]
self.neck = nn.Sequential(
nn.Conv2d(960, 576, kernel_size=1, stride=1, padding=0),
nn.BatchNorm2d(576),
nn.ReLU(inplace=True),
nn.Conv2d(576, 1280, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1280),
nn.ReLU(inplace=True),
nn.Conv2d(1280, 576, kernel_size=1, stride=1, padding=0),
nn.BatchNorm2d(576),
nn.ReLU(inplace=True),
nn.Conv2d(576, 1280, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1280),
nn.ReLU(inplace=True),
)
self.head = nn.Sequential(
nn.Conv2d(1280, 512, kernel_size=1, stride=1, padding=0),
nn.BatchNorm2d(512),
nn.ReLU(inplace=True),
nn.Conv2d(512, 1024, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1024),
nn.ReLU(inplace=True),
nn.Conv2d(1024, 512, kernel_size=1, stride=1, padding=0),
nn.BatchNorm2d(512),
nn.ReLU(inplace=True),
nn.Conv2d(512, 1024, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1024),
nn.ReLU(inplace=True),
nn.Conv2d(1024, 512, kernel_size=1, stride=1, padding=0),
nn.BatchNorm2d(512),
nn.ReLU(inplace=True),
nn.Conv2d(512, 1024, kernel_size=3, stride=1, padding=1),
nn.BatchNorm2d(1024),
nn.ReLU(inplace=True),
)
self.detect = Detect(num_classes=num_classes)
def forward(self, x):
x = self.backbone(x)
x = self.neck(x)
x = self.head(x)
return self.detect(x)
model = YoloV5MobileNet()
```
请注意,这是一个简单的示例,可能需要进一步的调整和修改以适合您的数据集和应用场景。此外,这个代码只适用于YoloV5的backbone使用CSPDarkNet53的情况。如果您使用的是其他backbone,可能需要进行更多的修改。
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