#-*-coding:utf-8-*- import numpy as np import matplotlib.pyplot as plt from data_utils import load_CIFAR10 cifar10_dir = 'datasets/cifar-10-batches-py' X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir) print("训练数据：",X_train.shape) classes = ['plane', 'cat', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck'] num_classes = len(classes) samples_per_class = 7 for y,cls in enumerate(classes): idxs = np.flatnonzero(y_train == y) idxs = np.random.choice(idxs,samples_per_class, replace=False) for i, idx in enumerate(idxs): plt_idx = i * num_classes + y + 1 plt.subplot(samples_per_class, num_classes, plt_idx) plt.imshow(X_train[idx].astype('uint8')) plt.axis('off') if i == 0: plt.title(cls) plt.show() 
文章来源: 使用cifar-10数据集