cifar100

อ้างอิง:

ซิฟาร์100

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:cifar100/cifar100')
  • คำอธิบาย :
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).
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชัน : 1.0.0
  • แยก :
แยก ตัวอย่าง
'test' 10,000
'train' 50,000
  • คุณสมบัติ :
{
    "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"
    }
}