This is a summary of datasets designed for image classification in deep learning.
Dataset | Number of samples | Number of classes | Ave per class | Image Size | Permute | Split | Combine |
---|---|---|---|---|---|---|---|
Arabic Handwritten Digits | 70,000 | 10 | 7,000 | 1x28x28 | y | MLP, 97 | |
Caltech 101 | 9,146 | 102 | 90 | Coloured, not aligned | y | ||
Caltech 256 | 30,607 | 257 | 119 | Coloured, not aligned | y | ||
CelebA | 202,599 | 10,177 | 20 | 3x178x218 | y | (too slow) | |
CIFAR-10 | 60,000 | 10 | 6,000 | 3x32x32 | y | ResNet18, 50 | |
CIFAR-100 | 60,000 | 100 | 600 | 3x32x32 | y | ResNet18, 47 | |
Country 211 | 62,200 | 211 | 300 | 3x256x256 | y | ResNet18, 50 | |
CUB-200-2011 | 120,000 | 200 | 600 | 3x64x64 | y | ||
DTD | 5,640 | 47 | 120 | Coloured, not aligned, 300x300- 640x640 | y | ||
EMNIST Balanced | 131,600 | 47 | 2800 | 1x28x28 | y | MLP, 82 | |
EMNIST ByClass | 814,255 | 62 | ~13000 | 1x28x28 | y | MLP, 84 | |
EMNIST ByMerge | 814,255 | 47 | ~17300 | 1x28x28 | y | MLP, 87 | |
EMNIST Digits | 280,000 | 10 | 28000 | 1x28x28 | y | MLP, 98 | |
EMNIST Letters | 145,600 | 26 | 5600 | 1x28x28 | y | MLP, 90 | |
EuroSAT | 27,000 | 10 | 2,700 | 3x64x64 | y | ResNet18, 93 | |
FaceScrub | 106,863 | 530 | 202 | Coloured, not aligned | |||
FaceScrub 10 Classes | ~10,000 | 10 | 1,000 | 3x32x32 | y | ResNet18, 89 | |
Fashion-MNIST | 70,000 | 10 | 7,000 | 1x28x28 | y | MLP, 86 | |
FER2013 | 35,887 | 7 | 5,127 | 1x48x48 | y | ||
FGVC-Aircraft By Family | 10,200 | 70 | 146 | Coloured, not aligned | y | ||
FGVC-Aircraft By Manufacturer | 10,200 | 41 | 249 | Coloured, not aligned | y | ||
FGVC-Aircraft By Variant | 10,200 | 102 | 100 | Coloured, not aligned | y | ||
Food-101 | 101,000 | 101 | 1,000 | Coloured, not aligned | y | ||
GTSRB | 51,839 | 43 | 1,205 | Coloured, not aligned | y | ResNet18, 80 | |
ImageNet | 1,281,167 | 1,000 | 1,281 | Coloured, not aligned | too large | ||
Imagenette | 130,000 | 10 | 13,000 | Coloured, not aligned (full size) / 3x320x320 / 3x160x160 | y | ||
iNaturalist | ~3,200,000 | 10,000 | ~320 | Coloured, not aligned | too large | ||
Kannada-MNIST | 70,000 | 10 | 7,000 | 1x28x28 | y | MLP, 93 | |
Kuzushiji-MNIST | 70,000 | 10 | 7,000 | 1x28x28 | y | MLP, 87 | |
LFW | ~13,000 | 5,749 | 2 | 3x250x250 | too few samples per class | ||
Linnaeus 5 | 8,000 | 5 | 1,600 | 3x256x256 / 3x128x128 / 3x64x64 / 3x32x32 | y | ResNet18, 54 | |
LSUN | ~10,000,000 | 10 | ~1,000,000 | Coloured, not aligned | |||
MedMNIST2D BloodMNIST | 17,092 | 8 | 2,136 | 1x28x28 | |||
MedMNIST2D BreastMNIST | 780 | 2 | 390 | 1x28x28 | |||
MedMNIST2D ChestMNIST | 112,120 | 2 | 56,060 | 1x28x28 | |||
MedMNIST2D DermaMNIST | 10,015 | 7 | 1,430 | 1x28x28 | |||
MedMNIST2D OCTMNIST | 109,309 | 4 | 27,327 | 1x28x28 | |||
MedMNIST2D OrganAMNIST | 58,830 | 11 | 5,348 | 1x28x28 | |||
MedMNIST2D OrganCMNIST | 23,583 | 11 | 2,144 | 1x28x28 | |||
MedMNIST2D OrganSMNIST | 25,211 | 11 | 2,283 | 1x28x28 | |||
MedMNIST2D PathMNIST | 107,180 | 9 | 11,000 | 1x28x28 | |||
MedMNIST2D PneumoniaMNIST | 5,856 | 2 | 2,928 | 1x28x28 | |||
MedMNIST2D TissueMNIST | 236,386 | 8 | 29,548 | 1x28x28 | |||
MNIST | 70,000 | 10 | 7,000 | 1x28x28 | y | MLP, 98 | |
notMNIST | Small ~19,000, Large ~500,000 | 10 | ~1,900, ~50,000 | 1x28x28 | y | MLP, 95 | |
Omniglot | 32,460 | 1,623 | 20 | 1x105x105 | |||
Oxford 102 Flowers | 8,189 | 102 | 80 | Coloured, not aligned | y | ResNet18, 62 | |
Oxford-IIIT Pet | 7,349 | 37 | ~200 | Coloured, not aligned | y | ||
PCAM | 327,680 | 2 | 163,840 | 3x96x96 | y | large 7G | |
Places365 | ~10,000,000 | 434 | ~23,000 | Coloured, not aligned | too large | ||
QMNIST | 120,000 | 10 | 12,000 | 1x28x28 | |||
Rendered SST2 | 9,613 | 2 | 4,806 | 3x448x448 | y | ||
Semeion Handwritten Digit | 1,593 | 10 | 159 | 1x16x16 | y | MLP, 90 | |
Sign Language MNIST | 34,627 | 24 | 1,148 | 1x28x28 | y | MLP, 60; | |
Stanford Cars | 16,185 | 196 | 82 | Coloured, not aligned | y | Download link broken | |
STL-10 | 13,000 + 100,000 unlabeled data | 10 | - | 3x96x96 | n | for unsupervised learning | |
SUN397 | 108,754 | 397 | 274 | Coloured, not aligned | y | 10G, too large | |
SVHN | 99,289 (without extra) | 10 | 9,929 | 3x32x32 | y | ResNet18, 90 | |
TinyImageNet | 120,000 | 200 | 600 | 3x64x64 | y | ResNet18, 70 (30 epochs) | |
USPS | 9,298 | 10 | 930 | 1x16x16 | y |