CIFAR-100 dataset

A training dataset of 50,000 32 x 32 pixel color images labeled over 100 categories and 10,000 test images, this dataset is similar to CIFAR-10, but it has 100 classes with 600 images in each class. Five-hundred training images and 100 testing images are in each class. The 100 classes in CIFAR-100 are grouped into 20 superclasses. Each image comes with a coarse label (the superclass to which it belongs) and a fine label (the class to which it belongs). A list of classes in CIFAR-100 is as follows:

Superclass	Classes
aquatic mammals	beaver, dolphin, otter, seal, and whale
fish	aquarium fish, flatfish, ray, shark, and trout
flowers	orchids, poppies, roses, sunflowers, and tulips
food containers	bottles, bowls, cans, cups, and plates
fruit and vegetables	apples, mushrooms, oranges, pears, and sweet peppers
household electrical devices	clock, computer keyboard, lamp, telephone, and television
household furniture	bed, chair, couch, table, and wardrobe
insects	bee, beetle, butterfly, caterpillar...