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作为主流的分类数据集,这一篇主要讲 CIFRA-10 与 CIFRA-100 数据集下载与Python版本的处理
数据集下载地址:http://www.cs.toronto.edu/~kriz/cifar.html
数据介绍
CIFAR-10和CIFAR-100是两组有8000万个微小图像数据组成的标记图片数据集。它们是由Alex Krizhevsky,Vinod Nair和Geoffrey Hinton(大佬大佬大佬)收集的。
CIFAR-10数据集
CIFAR-10数据集由10个类(‘airplane’, ‘automobile’, ‘bird’, ‘cat’, ‘deer’, ‘dog’, ‘frog’, ‘horse’, ‘ship’, ‘truck’)共60000个32x32彩色图像组成,每个类有6000个图像。被划分为50000个训练图像和10000个测试图像。
数据集分为五个训练批次(data_batch)和一个测试批次(test_batch),每个批次有10000个图像。测试批次包含来自每个类别的1000个随机选择的图像。训练批次以随机顺序包含剩余图像,但是一些训练批次可能包含来自一个类别的更多图像而不是另一个类别。在它们之间,训练批次包含来自每个类别的5000个图像。
下载地址
Version | Size | md5sum |
---|---|---|
CIFAR-10 python version | 163 MB | c58f30108f718f92721af3b95e74349a |
CIFAR-10 Matlab version | 175 MB | 70270af85842c9e89bb428ec9976c926 |
CIFAR-10 binary version (suitable for C programs) | 162 MB | c32a1d4ab5d03f1284b67883e8d87530 |
CIFRA-100数据集
此数据集与CIFAR-10类似,不同之处在于它有100个类,每个类包含600个图像。每类分为500个训练图像和100个测试图像。其中100个类分为20个大类。每个图像都带有一个“精细”标签(它所属的类)和一个“粗略”标签(它所属的大类)。
以下是CIFAR-100中的类列表:
Superclass | Classes |
---|---|
aquatic mammals | beaver, dolphin, otter, seal, whale |
fish | aquarium fish, flatfish, ray, shark, trout |
flowers | orchids, poppies, roses, sunflowers, tulips |
food containers | bottles, bowls, cans, cups, plates |
fruit and vegetables | apples, mushrooms, oranges, pears, sweet peppers |
household electrical devices | clock, computer keyboard, lamp, telephone, television |
household furniture | bed, chair, couch, table, wardrobe |
insects | bee, beetle, butterfly, caterpillar, cockroach |
large carnivores | bear, leopard, lion, tiger, wolf |
large man-made outdoor things | bridge, castle, house, road, skyscraper |
large natural outdoor scenes | cloud, forest, mountain, plain, sea |
large omnivores and herbivores | camel, cattle, chimpanzee, elephant, kangaroo |
medium-sized mammals | fox, porcupine, possum, raccoon, skunk |
non-insect invertebrates | crab, lobster, snail, spider, worm |
people | baby, boy, girl, man, woman |
reptiles | crocodile, dinosaur, lizard, snake, turtle |
small mammals | hamster, mouse, rabbit, shrew, squirrel |
trees | maple, oak, palm, pine, willow |
vehicles 1 | bicycle, bus, motorcycle, pickup truck, train |
vehicles 2 | lawn-mower, rocket, streetcar, tank, tractor |
下载地址
Version | Size | md5sum |
---|---|---|
CIFAR-100 python version | 161 MB | eb9058c3a382ffc7106e4002c42a8d85 |
CIFAR-100 Matlab version | 175 MB | 6a4bfa1dcd5c9453dda6bb54194911f4 |
CIFAR-100 binary version (suitable for C programs) | 161 MB | 03b5dce01913d631647c71ecec9e9cb8 |