# data.vision¶

Vision utilities.

## Datasets¶

 datasets.MNIST([root, train, transform]) MNIST handwritten digits dataset from http://yann.lecun.com/exdb/mnist datasets.FashionMNIST([root, train, transform]) A dataset of Zalando’s article images consisting of fashion products, a drop-in replacement of the original MNIST dataset from https://github.com/zalandoresearch/fashion-mnist datasets.CIFAR10([root, train, transform]) CIFAR10 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html datasets.CIFAR100([root, fine_label, train, …]) CIFAR100 image classification dataset from https://www.cs.toronto.edu/~kriz/cifar.html datasets.ImageRecordDataset(filename[, …]) A dataset wrapping over a RecordIO file containing images. datasets.ImageFolderDataset(root[, flag, …]) A dataset for loading image files stored in a folder structure.

## Data transformations¶

 transforms.Compose(transforms) Sequentially composes multiple transforms. transforms.Cast([dtype]) Cast input to a specific data type Converts an image NDArray to a tensor NDArray. transforms.Normalize(mean, std) Normalize an tensor of shape (C x H x W) with mean and standard deviation. transforms.RandomResizedCrop(size[, scale, …]) Crop the input image with random scale and aspect ratio. transforms.CenterCrop(size[, interpolation]) Crops the image src to the given size by trimming on all four sides and preserving the center of the image. transforms.Resize(size[, keep_ratio, …]) Resize an image to the given size. Randomly flip the input image left to right with a probability of 0.5. Randomly flip the input image top to bottom with a probability of 0.5. transforms.RandomBrightness(brightness) Randomly jitters image brightness with a factor chosen from [max(0, 1 - brightness), 1 + brightness]. transforms.RandomContrast(contrast) Randomly jitters image contrast with a factor chosen from [max(0, 1 - contrast), 1 + contrast]. transforms.RandomSaturation(saturation) Randomly jitters image saturation with a factor chosen from [max(0, 1 - saturation), 1 + saturation]. Randomly jitters image hue with a factor chosen from [max(0, 1 - hue), 1 + hue]. transforms.RandomColorJitter([brightness, …]) Randomly jitters the brightness, contrast, saturation, and hue of an image. Add AlexNet-style PCA-based noise to an image.