如何使用Pytorch中保存的模型来预测从未见过的图像的标签？

import torch
import torchvision.transforms as transforms
from PIL import Image

model = torch.load('model.pth')

transform = transforms.Compose([
    transforms.Resize((224, 224)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])

image = Image.open('image.jpg')
image = transform(image)
image = image.unsqueeze(0)

output = model(image)
_, predicted = torch.max(output, 1)

labels = ['class1', 'class2', 'class3']  # 替换为模型训练时使用的类别标签
predicted_label = labels[predicted.item()]
print(predicted_label)