load_cifar10_step2.py

import numpy as np

import os
import pickle

labels = ["airplane", "automobile", "bird", "cat", "deer",
              "dog", "frog", "horse", "ship", "truck"]

def load_cifar10():

    path = 'cifar-10-batches-py'

    if not os.path.exists(path):
        os.system("wget {}".format(path))
        os.system("tar xvf {}".format(path))

    # train data
    
    train_x = np.ndarray([0, 32, 32, 3], dtype=np.float32)
    train_y = np.ndarray([0, ], dtype=np.int)
    
    for i in range(1, 6):
        data_path = path + '/data_batch_{}'.format(i)
        with open(data_path, 'rb') as f:
            datas = pickle.load(f, encoding='bytes')
            print(data_path)
            x = datas[b'data']
            x = x.reshape(x.shape[0], 3, 32, 32)
            x = x.transpose(0, 2, 3, 1)
            train_x = np.vstack((train_x, x))
        
            y = np.array(datas[b'labels'], dtype=np.int)
            train_y = np.hstack((train_y, y))

    print(train_x.shape)
    print(train_y.shape)

load_cifar10()