将数据集与transforms结合

• 可以直接在PyCharm中下载数据集

import torchvision
from torch.utils.tensorboard import SummaryWriter
dataset_transform = torchvision.transforms.Compose([
    torchvision.transforms.ToTensor()
])
# train_dataset = torchvision.datasets.CIFAR10(root="./download_data",train=True,download=True)
# test_dataset = torchvision.datasets.CIFAR10(root="./download_data",train=False,download=True)
# 下载数据集，这其实是一个下载接口
train_dataset = torchvision.datasets.CIFAR10(root="./download_data",train=True,transform=dataset_transform,download=True)
test_dataset = torchvision.datasets.CIFAR10(root="./download_data",train=False,transform=dataset_transform,download=True)
'''
print(test_dataset[0])
print(test_dataset.classes)
img,target = test_dataset[0]
print(img)
print(target)
print(test_dataset.classes[target])
img.show()
'''
writer = SummaryWriter("test_data")
for i in range(10):
    img,target = test_dataset[i]
    writer.add_image("dataset",img,i)
writer.close()