Introduced by Xiao et al. in Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Fashion-MNIST is a dataset comprising of 28×28 grayscale images of 70,000 fashion products from 10 categories, with 7,000 images per category. The training set has 60,000 images and the test set has 10,000 images. Fashion-MNIST shares the same image size, data format and the structure of training and testing splits with the original MNIST.
Source: Generative Probabilistic Novelty Detection with Adversarial Autoencoders