Dateset和Datloader类
@疏锦行
import torch import torchvision import torchvision.transforms as transforms import matplotlib.pyplot as plt import numpy as np #1.定义数据预处理（转为 Tensor） transform=transforms.ToTensor()#2.下载并加载 CIFAR-10训练集 cifar10_dataset=torchvision.datasets.CIFAR10(root='./data',train=True,download=True,transform=transform)#3.取出一张图片和对应标签 image,label=cifar10_dataset[0]# CIFAR-10类别名称 classes=('airplane','automobile','bird','cat','deer','dog','frog','horse','ship','truck')print("Label index:",label)print("Label name:",classes[label])print("Image shape:",image.shape)#[3,32,32]#4.Tensor → NumPy，并调整维度以便显示 image_np=image.permute(1,2,0).numpy()#5.显示图片 plt.imshow(image_np)plt.title(classes[label])plt.axis('off')plt.show()
