从Torchvision预训练模型中获取模型类标签

如何解决从Torchvision预训练模型中获取模型类标签

我使用的是Torchvision提供的经过预先训练的Alexnet模型（无微调）。 问题是，即使我能够对某些数据运行模型并获得输出概率分布，也无法找到将其映射到的类标签。

import torch
model = torch.hub.load('pytorch/vision:v0.6.0','alexnet',pretrained=True)
model.eval()

AlexNet(
  (features): Sequential(
    (0): Conv2d(3,64,kernel_size=(11,11),stride=(4,4),padding=(2,2))
    (1): ReLU(inplace=True)
    (2): MaxPool2d(kernel_size=3,stride=2,padding=0,dilation=1,ceil_mode=False)
    (3): Conv2d(64,192,kernel_size=(5,5),stride=(1,1),2))
    (4): ReLU(inplace=True)
    (5): MaxPool2d(kernel_size=3,ceil_mode=False)
    (6): Conv2d(192,384,kernel_size=(3,3),padding=(1,1))
    (7): ReLU(inplace=True)
    (8): Conv2d(384,256,1))
    (9): ReLU(inplace=True)
    (10): Conv2d(256,1))
    (11): ReLU(inplace=True)
    (12): MaxPool2d(kernel_size=3,ceil_mode=False)
  )
  (avgpool): AdaptiveAvgPool2d(output_size=(6,6))
  (classifier): Sequential(
    (0): Dropout(p=0.5,inplace=False)
    (1): Linear(in_features=9216,out_features=4096,bias=True)
    (2): ReLU(inplace=True)
    (3): Dropout(p=0.5,inplace=False)
    (4): Linear(in_features=4096,bias=True)
    (5): ReLU(inplace=True)
    (6): Linear(in_features=4096,out_features=1000,bias=True)
  )
)

按照一些处理图像的步骤，我能够使用它来获取单个图像的输出，作为（1,1000）暗淡矢量，我将使用softmax来获得概率分布-

#Output - 

tensor([-1.6531e+00,-4.3505e+00,-1.8172e+00,-4.2143e+00,-3.1914e+00,3.4163e-01,1.0877e+00,5.9350e+00,8.0425e+00,-7.0242e-01,-9.4130e-01,-6.0822e-01,-2.4097e-01,-1.9946e+00,-1.5288e+00,-3.2656e+00,-5.5800e-01,1.0524e+00,1.9211e-01,-4.7202e+00,-3.3880e+00,4.3048e+00,-1.0997e+00,4.6132e+00,-5.7404e-03,-5.3437e+00,-4.7378e+00,-3.3974e+00,-4.1287e+00,2.9064e-01,-3.2955e+00,-6.7051e+00,-4.7232e+00,-4.1778e+00,-2.1859e+00,-2.9469e+00,3.0465e+00,-3.5882e+00,-6.3890e+00,-4.4203e+00,-3.3685e+00,-5.0983e+00,-4.9006e+00,-5.5235e+00,-3.7233e+00,-4.0204e+00,2.6998e-01,-4.4702e+00,-5.6617e+00,-5.4880e+00,-2.6801e+00,-3.2129e+00,-1.6294e+00,-5.2289e+00,-2.7495e+00,-2.6286e+00,-1.8206e+00,-2.3196e+00,-5.2806e+00,-3.7652e+00,-3.0987e+00,-4.1421e+00,-5.2531e+00,-4.6505e+00,-3.5815e+00,-4.0189e+00,-4.0008e+00,-4.5512e+00,-3.2248e+00,-7.7903e+00,-1.4484e+00,-3.8347e+00,-4.5611e+00,-4.3681e+00,2.7234e-01,-4.0162e+00,-4.2136e+00,-5.4524e+00,1.1744e+00,-4.7785e+00,-1.8335e+00,4.1288e-01,2.2239e+00,-9.9919e-02,4.8216e+00,-8.4304e-01,5.6911e-01,-4.0484e+00,-3.3013e+00,2.8698e+00,-1.1419e+00,-9.1690e-01,-2.9284e+00,-2.6097e+00,-1.8213e-01,-2.5429e+00,-2.1095e+00,2.2419e+00,-1.6280e+00,7.4458e+00,2.3184e+00,-5.7408e+00,-7.4332e-01,-5.4066e+00,1.5177e+01,-4.4737e-02,1.8237e+00,-3.7741e+00,9.2271e-01,-4.3687e-01,-1.4003e+00,-4.3026e+00,6.3782e-01,-1.0808e+00,-1.4173e+00,2.6194e+00,-3.8418e+00,1.1598e+00,-2.6876e+00,-3.6103e+00,-4.9281e+00,-4.1411e+00,-3.3603e+00,-3.4296e+00,-1.4997e+00,-2.8381e+00,-1.2843e+00,1.5745e+00,-1.7449e+00,4.2903e-01,3.1234e-01,-2.8206e+00,3.6688e-01,-2.1033e+00,1.6481e+00,1.4222e+00,-2.7303e+00,-3.6292e+00,1.2864e+00,-2.5541e+00,-2.9663e+00,-4.1575e+00,-3.1954e+00,-4.6487e-01,1.8916e+00,-7.4721e-01,4.5986e+00,-2.5443e+00,-6.2003e+00,-1.3215e+00,-2.6225e+00,9.9639e+00,9.7772e+00,9.6715e+00,9.0857e+00,...

我从哪里获得课程标签？我找不到任何可以从模型对象中获取方法的方法。

解决方法

不幸的是，您不能直接从Torchvision模型获取类标签名称。但是，这些模型是在ImageNet数据集上训练的（因此有1000个类）。

据我所知，您必须从网络上获取类名映射；没有办法把它从火炬上拿下来。以前，您可以使用torchvision.datasets.ImageNet直接下载ImageNet，它具有一个内置的标签到类名转换器。现在，下载链接不再公开可用，需要手动下载，然后才能被数据集使用。ImageNet。

因此，您可以简单地在线搜索类以标记ImageNet的标签，而无需下载数据或尝试使用手电筒。 Try here for example。

从Torchvision预训练模型中获取模型类标签

如何解决从Torchvision预训练模型中获取模型类标签

解决方法

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