目录
2.将test_MobileNetV3.py上面的代码复制粘贴到如下文件里面
1. 宽度为0.5的YOLOV5网络的结构图
在主干网络上面可以重新定义成三层,编号从0开始
如图是MobileNetV3 的网络结构,要想重新定义的画需要保持每次输出图片的大小不变
定义MobileNetV3 的代码如下,我们可以分为3层 test_MobileNetV3.py
- import torch
- from torch import nn
- from torchvision import models
- from torchinfo import summary
- class MobileNetV3(nn.Module):
- def __init__(self, n):
- super().__init__()
- model = models.mobilenet_v3_small(pretrained=True)
- if n == 0:
- self.model = model
- if n == 1:
- self.model = model.features[:4]
- if n == 2:
- self.model = model.features[4:9]
- if n == 3:
- self.model = model.features[9:]
-
- def forward(self, x):
- return self.model(x)
-
- if __name__ == '__main__':
- x = torch.randn(1, 3, 640, 640)
- net = MobileNetV3(0)
- out = net(x)
- print(x.shape)
- summary(net,(1,3,640,640))
feature代表的含义
从这些里面挑一个
做出如下更改
- # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-
- # Parameters
- nc: 80 # number of classes
- depth_multiple: 0.33 # model depth multiple
- width_multiple: 0.50 # layer channel multiple
- anchors:
- - [10,13, 16,30, 33,23] # P3/8
- - [30,61, 62,45, 59,119] # P4/16
- - [116,90, 156,198, 373,326] # P5/32
-
- # YOLOv5 v6.0 backbone
- backbone:
- # [from, number, module, args]
- [
- [-1, 1,MobileNetV3, [24, 1]], # 0-P1/2
- [-1, 1,MobileNetV3, [48,2]], # 1-P2/4
- [-1, 1,MobileNetV3, [576,3]],
- ]
-
- # YOLOv5 v6.0 head
- head:
- [[-1, 1, Conv, [512, 1, 1]],
- [-1, 1, nn.Upsample, [None, 2, 'nearest']],
- [[-1, 1], 1, Concat, [1]], # cat backbone P4
- [-1, 3, C3, [512, False]], # 13
-
- [-1, 1, Conv, [256, 1, 1]],
- [-1, 1, nn.Upsample, [None, 2, 'nearest']],
- [[-1, 0], 1, Concat, [1]], # cat backbone P3
- [-1, 3, C3, [256, False]], # 17 (P3/8-small)
-
- [-1, 1, Conv, [256, 3, 2]],
- [[-1, 7], 1, Concat, [1]], # cat head P4
- [-1, 3, C3, [512, False]], # 20 (P4/16-medium)
-
- [-1, 1, Conv, [512, 3, 2]],
- [[-1, 3], 1, Concat, [1]], # cat head P5
- [-1, 3, C3, [1024, False]], # 23 (P5/32-large)
-
- [[10, 13, 16], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
- ]
下面几张图是解释
如下位置
添加如下代码,大概340行左右
还是在yolo.py文件里面更改这一句可以进行测试
run一下yolo.py
更改完成!!!