DAY 42 Dataset和Dataloader类

import torch from torchvision import datasets, transforms # torchvision 是一个用于计算机视觉的库，datasets 和 transforms 是其中的模块 import matplotlib.pyplot as plt transform = transforms.Compose([ transforms.ToTensor(), # 转换为张量并归一化到[0,1] ]) dataset = datasets.CIFAR10( root='./data', train=True, download=True, transform=transform ) sample_idx = torch.randint(0, len(dataset), size=(1,)).item() # 随机选择一张图片的索引 image, label = dataset[sample_idx] # print(image) def imshow(img, label): img = img.permute(1, 2, 0) plt.imshow(img) plt.title(f"Label: {dataset.classes[label]}") plt.axis('off') plt.show() print(f"Label: {label}") imshow(image, label)

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