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*Memos:
- My post explains MNIST, EMNIST, QMNIST, ETLCDB, Kuzushiji and Moving MNIST.
- My post explains Fashion-MNIST, Caltech 101, Caltech 256, CelebA, CIFAR-10 and CIFAR-100.
(1) Oxford-IIIT Pet(2012):
- has the 7,349 cat and dog images each connected to the label from 37 classes:
*Memos:
- Each class has roughly 200 images.
- 3,680 for train or train and validation and 3,669 for test.
- is OxfordIIITPet() in PyTorch.
(2) Oxford 102 Flower(2008):
- has 8,189 flower images(1,020 for train, 1,020 for validation and 6,149 for test) with the 102 categories(classes). *Each class has 40 to 258 images.
- is Flowers102() in PyTorch.
(3) Stanford Cars(2013):
- has 16185 car images(8,144 for train and 8,041 for test) with 196 classes.
- is StanfordCars() in PyTorch.
(4) Places365(2017):
- has scene images with the 365 scene categories(classes) out of the 434 scene categories(classes) in the Places Database and there are Places365-Standard, Places365-Challenge and Places-Extra69 as you can see here:
*Memos:
- Places365-Standard has 2,168,460 images(1,803,460 for train, 36,500 for validation and 328,500 for test) with the 365 categories(classes) out of the 434 categories(classes) in the Places Database. *There are 50 images per category(class) in the validation set and 900 images per category(class) in the test set.
- Places365-Challenge has 8,391,628 images(8,026,628 for train, 36,500 for validation and 328,500 for test), adding 6,223,168 extra images to the train set of Places365-Standard.
- Places-Extra69 has 105,321 images(98,721 for train and 6,600 for test) with the extra 69 categories(classes) out of the 434 categories(classes) in the Places Database. *Currently, it cannot be downloaded.
- is Places365() in PyTorch.
(5) Flickr8k(2013):
- has the 8,091 images obtained from flickr with the five different captions for each image.
- is Flickr8k() in PyTorch but it doesn't explain how to set up the dataset to it so I don't know how to load the dataset with it.
(6) Flickr30k(2015):
- has 31,784 images obtained from flickr with the five different captions for each image.
- is Flickr8k() in PyTorch but it doesn't explain how to set up the dataset to it so I don't know how to load the dataset with it.
The above is the detailed content of Datasets for Computer Vision (3). For more information, please follow other related articles on the PHP Chinese website!

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