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#实战AlexNet迁移学习的图片识别
#数据预处理设置
import torch
import torchvision
from torchvision import datasets,transforms
import matplotlib.pyplot as plt
import os


os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'# 预处理设置


data_transforms = {
  "train":transforms.Compose([
    transforms.Resize(230),  # 自适应缩小到最大边长为230的大小
    transforms.CenterCrop(224), # 居中裁切,此处的224是为了适应后面的alexnet网络
    transforms.RandomHorizontalFlip(), # 随机水平翻转
    transforms.ToTensor(),
    transforms.Normalize([0.5,0.5,0.5],[0.5,0.5,0.5]) # 归一化
   ]),
  "test":transforms.Compose([
    transforms.Resize(256),
    transforms.CenterCrop(224),
    transforms.ToTensor(),
    transforms.Normalize([0.5,0.5,0.5],[0.5,0.5,0.5]) # 归一化
   ])
}