svtr 识别 pytorch
时间: 2023-11-15 22:06:36 浏览: 159
可以使用以下代码来识别SVTR(Spatial Variance of Texture and Reflectance):
```python
import torch
import torch.nn as nn
import torchvision.models as models
class SVTR(nn.Module):
def __init__(self):
super(SVTR, self).__init__()
self.vgg = models.vgg16(pretrained=True).features[:23]
self.avgpool = nn.AdaptiveAvgPool2d(output_size=(1, 1))
self.fc = nn.Linear(512, 1)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
x = self.vgg(x)
x = self.avgpool(x)
x = x.view(x.size(0), -1)
x = self.fc(x)
x = self.sigmoid(x)
return x
```
其中,使用了预训练的VGG16模型,前23层作为特征提取器,后接自适应平均池化层、全连接层和sigmoid激活函数。通过调用SVTR()函数即可得到模型。