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# CIFAR
from .cifar10 import CIFAR101, CIFAR102
# Small
from .collections import (
CIFAR10,
CIFAR100,
DTD,
MNIST,
SUN397,
Aircraft,
Caltech101,
EuroSAT,
Flowers,
Food,
OxfordPet,
StanfordCars,
)
from .fmow import FMOW, FMOWID, FMOWOOD
# ImageNet
from .imagenet import ImageNet
from .imagenet_a import ImageNetA
from .imagenet_r import ImageNetR
from .imagenet_sketch import ImageNetSketch
from .imagenet_small import ImageNetSM
from .imagenet_sub import ImageNetSUB
from .imagenet_subclass import ImageNetSC
from .imagenet_vid_robust import ImageNetVidRobust
from .imagenetv2 import ImageNetV2
from .iwildcam import (
IWildCam,
IWildCamID,
IWildCamIDNonEmpty,
IWildCamOOD,
IWildCamOODNonEmpty,
)
from .joint import Joint
# Random Noise
from .noise import Noise
from .objectnet import ObjectNet
from .ytbb_robust import YTBBRobust
# Experimental datasets
dataset_list = [
Aircraft,
Caltech101,
CIFAR10,
CIFAR100,
DTD,
EuroSAT,
Flowers,
Food,
MNIST,
OxfordPet,
StanfordCars,
SUN397,
]
def show_datasets():
print("Total: ", len(dataset_list))
print("Dataset: (train_len, test_len, num_classes)")
for dataset in dataset_list:
d = dataset(None)
print(f"{d.name}: ", d.stats())
for i in range(3):
print(f"T[{i}]: ", d.template(d.classnames[i]))
from .cc import conceptual_captions
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