سيفار 100

ds = tfds.load('huggingface:cifar100/cifar100')

The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).

{
    "img": {
        "id": null,
        "_type": "Image"
    },
    "fine_label": {
        "num_classes": 100,
        "names": [
            "apple",
            "aquarium_fish",
            "baby",
            "bear",
            "beaver",
            "bed",
            "bee",
            "beetle",
            "bicycle",
            "bottle",
            "bowl",
            "boy",
            "bridge",
            "bus",
            "butterfly",
            "camel",
            "can",
            "castle",
            "caterpillar",
            "cattle",
            "chair",
            "chimpanzee",
            "clock",
            "cloud",
            "cockroach",
            "couch",
            "cra",
            "crocodile",
            "cup",
            "dinosaur",
            "dolphin",
            "elephant",
            "flatfish",
            "forest",
            "fox",
            "girl",
            "hamster",
            "house",
            "kangaroo",
            "keyboard",
            "lamp",
            "lawn_mower",
            "leopard",
            "lion",
            "lizard",
            "lobster",
            "man",
            "maple_tree",
            "motorcycle",
            "mountain",
            "mouse",
            "mushroom",
            "oak_tree",
            "orange",
            "orchid",
            "otter",
            "palm_tree",
            "pear",
            "pickup_truck",
            "pine_tree",
            "plain",
            "plate",
            "poppy",
            "porcupine",
            "possum",
            "rabbit",
            "raccoon",
            "ray",
            "road",
            "rocket",
            "rose",
            "sea",
            "seal",
            "shark",
            "shrew",
            "skunk",
            "skyscraper",
            "snail",
            "snake",
            "spider",
            "squirrel",
            "streetcar",
            "sunflower",
            "sweet_pepper",
            "table",
            "tank",
            "telephone",
            "television",
            "tiger",
            "tractor",
            "train",
            "trout",
            "tulip",
            "turtle",
            "wardrobe",
            "whale",
            "willow_tree",
            "wolf",
            "woman",
            "worm"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "coarse_label": {
        "num_classes": 20,
        "names": [
            "aquatic_mammals",
            "fish",
            "flowers",
            "food_containers",
            "fruit_and_vegetables",
            "household_electrical_devices",
            "household_furniture",
            "insects",
            "large_carnivores",
            "large_man-made_outdoor_things",
            "large_natural_outdoor_scenes",
            "large_omnivores_and_herbivores",
            "medium_mammals",
            "non-insect_invertebrates",
            "people",
            "reptiles",
            "small_mammals",
            "trees",
            "vehicles_1",
            "vehicles_2"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}