DATASET_CONSTANTS.py

CIFAR_10_CLASSES = 10
CIFAR_100_CLASSES = 100
CIFAR10_LABEL_MAPPING = {
    0: 'airplane',
    1: 'automobile',
    2: 'bird',
    3: 'cat',
    4: 'deer',
    5: 'dog',
    6: 'frog',
    7: 'horse',
    8: 'ship',
    9: 'truck'
}

CIFAR100_LABEL_MAPPING = {
    0: "apple",
    1: "aquarium_fish",
    2: "baby",
    3: "bear",
    4: "beaver",
    5: "bed",
    6: "bee",
    7: "beetle",
    8: "bicycle",
    9: "bottle",
    10: "bowl",
    11: "boy",
    12: "bridge",
    13: "bus",
    14: "butterfly",
    15: "camel",
    16: "can",
    17: "castle",
    18: "caterpillar",
    19: "cattle",
    20: "chair",
    21: "chimpanzee",
    22: "clock",
    23: "cloud",
    24: "cockroach",
    25: "couch",
    26: "cra",
    27: "crocodile",
    28: "cup",
    29: "dinosaur",
    30: "dolphin",
    31: "elephant",
    32: "flatfish",
    33: "forest",
    34: "fox",
    35: "girl",
    36: "hamster",
    37: "house",
    38: "kangaroo",
    39: "keyboard",
    40: "lamp",
    41: "lawn_mower",
    42: "leopard",
    43: "lion",
    44: "lizard",
    45: "lobster",
    46: "man",
    47: "maple_tree",
    48: "motorcycle",
    49: "mountain",
    50: "mouse",
    51: "mushroom",
    52: "oak_tree",
    53: "orange",
    54: "orchid",
    55: "otter",
    56: "palm_tree",
    57: "pear",
    58: "pickup_truck",
    59: "pine_tree",
    60: "plain",
    61: "plate",
    62: "poppy",
    63: "porcupine",
    64: "possum",
    65: "rabbit",
    66: "raccoon",
    67: "ray",
    68: "road",
    69: "rocket",
    70: "rose",
    71: "sea",
    72: "seal",
    73: "shark",
    74: "shrew",
    75: "skunk",
    76: "skyscraper",
    77: "snail",
    78: "snake",
    79: "spider",
    80: "squirrel",
    81: "streetcar",
    82: "sunflower",
    83: "sweet_pepper",
    84: "table",
    85: "tank",
    86: "telephone",
    87: "television",
    88: "tiger",
    89: "tractor",
    90: "train",
    91: "trout",
    92: "tulip",
    93: "turtle",
    94: "wardrobe",
    95: "whale",
    96: "willow_tree",
    97: "wolf",
    98: "woman",
    99: "worm"
}