python代码载入stl10数据集的训练集和测试集,并保存为npy文件

可以的，以下是Python代码载入stl10数据集的训练集和测试集，并保存为npy文件的示例：

import numpy as np
import os
import urllib.request
import tarfile
from PIL import Image

def download_data():
    url = 'http://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz'
    if not os.path.isfile('stl10_binary.tar.gz'):
        urllib.request.urlretrieve(url, 'stl10_binary.tar.gz')
    if not os.path.isdir('stl10_binary'):
        with tarfile.open('stl10_binary.tar.gz') as tar:
            tar.extractall()

def read_data(split):
    path = 'stl10_binary'
    if split == 'train':
        filename = os.path.join(path, 'train_X.bin')
        with open(filename, 'rb') as f:
            X_train = np.fromfile(f, dtype=np.uint8)
            X_train = np.reshape(X_train, (-1,3,96,96))
            X_train = np.transpose(X_train, (0,3,2,1))
        filename = os.path.join(path, 'train_y.bin')
        with open(filename, 'rb') as f:
            y_train = np.fromfile(f, dtype=np.uint8)
        return X_train, y_train
    elif split == 'test':
        filename = os.path.join(path, 'test_X.bin')
        with open(filename, 'rb') as f:
            X_test = np.fromfile(f, dtype=np.uint8)
            X_test = np.reshape(X_test, (-1,3,96,96))
            X_test = np.transpose(X_test, (0,3,2,1))
        filename = os.path.join(path, 'test_y.bin')
        with open(filename, 'rb') as f:
            y_test = np.fromfile(f, dtype=np.uint8)
        return X_test, y_test

def save_data(X, y, filename):
    np.save(filename, {'X': X, 'y': y})

if __name__ == '__main__':
    download_data()
    X_train, y_train = read_data('train')
    X_test, y_test = read_data('test')
    save_data(X_train, y_train, 'train.npy')
    save_data(X_test, y_test, 'test.npy')

这段代码会首先下载STL10数据集的压缩文件，然后解压出训练集和测试集的图像和标签，并转换为numpy数组的格式，并将其保存为npy文件。