torchvision (version 0.7.0)

mnist_dataset: MNIST and Derived Datasets

Description

Prepares various MNIST-style image classification datasets and optionally downloads them. Images are thumbnails images of 28 x 28 pixels of grayscale values encoded as integer.

Usage

mnist_dataset(
  root = tempdir(),
  train = TRUE,
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)
kmnist_dataset(
  root = tempdir(),
  train = TRUE,
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)
qmnist_dataset(
  root = tempdir(),
  split = "train",
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)
fashion_mnist_dataset(
  root = tempdir(),
  train = TRUE,
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)
emnist_dataset(
  root = tempdir(),
  split = "balanced",
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)

Value

A torch dataset object, where each items is a list of x (image) and y (label).

Arguments

root

Root directory for dataset storage. The dataset will be stored under root/<dataset-name>. Defaults to tempdir().

train

Logical. If TRUE, use the training set; otherwise, use the test set. Not applicable to all datasets.

transform

Optional. A function that takes an image and returns a transformed version (e.g., normalization, cropping).

target_transform

Optional. A function that transforms the label.

download

Logical. If TRUE, downloads the dataset to root/. If the dataset is already present, download is skipped.

split

Character. Used in emnist_dataset() and qmnist_dataset() to specify the subset. See individual descriptions for valid values.

Functions

• kmnist_dataset(): Kuzushiji-MNIST cursive Japanese character dataset.

• qmnist_dataset(): Extended MNIST dataset with high-precision test data (QMNIST).

• fashion_mnist_dataset(): Fashion-MNIST clothing image dataset.

• emnist_dataset(): EMNIST dataset with digits and letters and multiple split modes.

Supported Splits for <code>emnist_dataset()</code>

• "byclass": 62 classes (digits + uppercase + lowercase)

• "bymerge": 47 classes (merged uppercase and lowercase)

• "balanced": 47 classes, balanced digits and letters

• "letters": 26 uppercase letters

• "digits": 10 digit classes

• "mnist": Standard MNIST digit classes

Supported Splits for <code>qmnist_dataset()</code>

• "train": 60,000 training samples (MNIST-compatible)

• "test": Extended test set

• "nist": Full NIST digit set

Details

• MNIST: Original handwritten digit dataset.

• Fashion-MNIST: Clothing item images for classification.

• Kuzushiji-MNIST: Japanese cursive character dataset.

• QMNIST: Extended MNIST with high-precision NIST data.

• EMNIST: Letters and digits with multiple label splits.

See Also

Other classification_dataset: caltech_dataset, cifar10_dataset(), eurosat_dataset(), fer_dataset(), fgvc_aircraft_dataset(), flowers102_dataset(), oxfordiiitpet_dataset(), tiny_imagenet_dataset()

Examples

if (FALSE) {
ds <- mnist_dataset(download = TRUE)
item <- ds[1]
item$x  # image
item$y  # label

qmnist <- qmnist_dataset(split = "train", download = TRUE)
item <- qmnist[1]
item$x
item$y

emnist <- emnist_dataset(split = "balanced", download = TRUE)
item <- emnist[1]
item$x
item$y

kmnist <- kmnist_dataset(download = TRUE)
fmnist <- fashion_mnist_dataset(download = TRUE)
}