我找不到 ILSVRC2012 训练集的 URL 文本文件，但对于完整的 imagenet，您只能将 URL 下载为文本文件：http: //image-net.org/download

我编写了以下脚本来感受数据：

#!/usr/bin/env python

"""Analyze the distribution of classes in ImageNet."""

classes = {}
images = 0

with open("fall11_urls.txt") as f:
    for i, line in enumerate(f):
        label, _ = line.split("\t", 1)
        wnid, _ = label.split("_")
        if wnid in classes:
            classes[wnid] += 1
        else:
            classes[wnid] = 1
        images += 1

# Output
print("Classes: %i" % len(classes))
print("Images: %i" % images)

class_counts = [count for _, count in classes.items()]
import matplotlib.pyplot as plt
plt.hist(class_counts, bins=range(max(class_counts)))
plt.show()

这给了：

Classes: 21841
Images: 14197122

少于 100 个示例的类几乎没有用处。让我们从情节中删除它们。还将 bin 大小增加到 25：

#!/usr/bin/env python

"""Analyze the distribution of classes in ImageNet."""

classes = {}
images = 0

with open("fall11_urls.txt") as f:
    for i, line in enumerate(f):
        label, _ = line.split("\t", 1)
        wnid, _ = label.split("_")
        if wnid in classes:
            classes[wnid] += 1
        else:
            classes[wnid] = 1
        images += 1

# Output
print("Classes: %i" % len(classes))
print("Images: %i" % images)

class_counts = [count for _, count in classes.items()]
import matplotlib.pyplot as plt
plt.title('ImageNet class distribution')
plt.xlabel('Amount of available images')
plt.ylabel('Number of classes')
min_examples = 100
bin_size = 25
plt.hist(class_counts, bins=range(min_examples, max(class_counts), bin_size))
plt.show()

或使用 seaborn：

import seaborn as sns
sns.distplot(class_counts, kde=True, rug=False);
sns.plt.show()

前10名

数据最多的前 10 个类别是：

top10 = sorted(classes.items(), key=lambda n: n[1], reverse=True)[:10]
for class_label, count in top10:
    print("%s:\t%i" % (class_label, count))

n02094433:    3047 (Yorkshire terrier)
n02086240:    2563 (Shih-Tzu)
n01882714:    2469 (koala bear, kangaroo bear, native bear, )
n02087394:    2449 (Rhodesian ridgeback)
n02100735:    2426 (English setter)
n00483313:    2410 (singles)
n02279972:    2386 (monarch butterfly, Danaus plexippus)
n09428293:    2382 (seashore)
n02138441:    2341 (meerkat)
n02100583:    2334 (vizsla, Hungarian pointer)

使用http://www.image-net.org/api/text/wordnet.synset.getwords?wnid=n02094433您可以查找名称。