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.
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
)
Root directory for dataset storage. The dataset will be stored under root/<dataset-name>
. Defaults to tempdir()
.
Logical. If TRUE, use the training set; otherwise, use the test set. Not applicable to all datasets.
Optional. A function that takes an image and returns a transformed version (e.g., normalization, cropping).
Optional. A function that transforms the label.
Logical. If TRUE, downloads the dataset to root/
. If the dataset is already present, download is skipped.
Character. Used in emnist_dataset()
and qmnist_dataset()
to specify the subset. See individual descriptions for valid values.
A torch dataset object, where each items is a list of x
(image) and y
(label).
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.
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.
emnist_dataset()
"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
qmnist_dataset()
"train"
: 60,000 training samples (MNIST-compatible)
"test"
: Extended test set
"nist"
: Full NIST digit set
Other classification_dataset:
caltech_dataset
,
cifar10_dataset()
,
eurosat_dataset()
,
fer_dataset()
,
fgvc_aircraft_dataset()
,
flowers102_dataset()
,
oxfordiiitpet_dataset()
,
tiny_imagenet_dataset()
if (FALSE) { # \dontrun{
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)
} # }