效果演示图如下：

代码按照顺序运行即可

 vgg训练模型的代码如下：

import torch
from PIL import Image
from torchvision import datasets, models, transforms,utils
import torch.nn as nn
import numpy as np
import random
import os
import torchvision
from tqdm import tqdm

#设置随机种子

def setup_seed(seed):
   torch.manual_seed(seed)
   torch.cuda.manual_seed(seed)
   torch.cuda.manual_seed_all(seed)
   np.random.seed(seed)
   random.seed(seed)
   torch.backends.cudnn.benchmark = False
   torch.backends.cudnn.deterministic = True
   torch.backends.cudnn.enabled = True
   os.environ['PYTHONHASHSEED'] = str(seed)
setup_seed(20)

root = './'

# Hyper parameters
num_epochs = 3    #循环次数
batch_size = 2 #每次投喂数据量
learning_rate = 0.00005   #学习率
momentum = 0.9  #变化率
num_classes = 2 #几分类