Table Of Contents
Table Of Contents

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

transforms.ToTensor()

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.

transforms.RandomFlipLeftRight()

Randomly flip the input image left to right with a probability of 0.5.

transforms.RandomFlipTopBottom()

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].

transforms.RandomHue(hue)

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.

transforms.RandomLighting(alpha)

Add AlexNet-style PCA-based noise to an image.