1. 从网络端下载 FashionMNIST 数据集到本地
(base) PS C:\Users\孙明阳> conda activate yang
(yang) PS C:\Users\孙明阳> python
Python 3.11.5 | packaged by Anaconda, Inc. | (main, Sep 11 2023, 13:26:23) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> from torchvision import datasets
>>> from torch.utils.data import Dataset
>>> from torchvision.transforms import ToTensor
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>>
>>> training_data = datasets.FashionMNIST(
... root="data/FashionMNIST/",
... train=True,
... download=True,
... transform=ToTensor()
... )
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\train-images-idx3-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\train-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\train-labels-idx1-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\train-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\t10k-images-idx3-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\t10k-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\t10k-labels-idx1-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\t10k-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
文章来源:https://www.toymoban.com/news/detail-784996.html
2. 数据集可视化
(base) PS C:\Users\阳> conda activate yang
(yang) PS C:\Users\阳> python
Python 3.11.5 | packaged by Anaconda, Inc. | (main, Sep 11 2023, 13:26:23) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> from torchvision import datasets
>>> from torch.utils.data import Dataset
>>> from torchvision.transforms import ToTensor
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> training_data = datasets.FashionMNIST(
... root="data/FashionMNIST/",
... train=True,
... download=True,
... transform=ToTensor()
... )
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\train-images-idx3-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\train-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\train-labels-idx1-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\train-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\t10k-images-idx3-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\t10k-images-idx3-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz
Downloading http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw\t10k-labels-idx1-ubyte.gz
100.0%
Extracting data/FashionMNIST/FashionMNIST\raw\t10k-labels-idx1-ubyte.gz to data/FashionMNIST/FashionMNIST\raw
>>> labels_map = {
... 0: "T-Shirt",
... 1: "Trouser",
... 2: "Pullover",
... 3: "Dress",
... 4: "Coat",
... 5: "Sandal",
... 6: "Shirt",
... 7: "Sneaker",
... 8: "Bag",
... 9: "Ankle Boot",
... }
>>> figure = plt.figure(figsize=(7, 7))
>>> cols, rows = 3, 3
>>> # 根据数据集的数据量len(training_data),随机生成9个位置坐标
>>> positions = np.random.randint(0, len(training_data), (9,))
>>> for i in range(9):
... img, label = training_data[positions[i]]
... plt.subplot(rows, cols, i + 1)
... plt.tight_layout(pad=0.05)
... # 每个子图的标题设置为对应图像的标签
... plt.title(labels_map[label])
... plt.axis("off")
... plt.imshow(img.squeeze(), cmap="gray")
>>> plt.savefig("D:\\fashion_mnist2.png")
>>> plt.show()
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