pythonstudy Day42

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()