fer_dataset: FER-2013 Facial Expression Dataset

In torchvision: Models, Datasets and Transformations for Images

FER-2013 Facial Expression Dataset

Description

Loads the FER-2013 dataset for facial expression recognition. The dataset contains grayscale images (48x48) of human faces, each labeled with one of seven emotion categories: "Angry", "Disgust", "Fear", "Happy", "Sad", "Surprise", and "Neutral".

Usage

fer_dataset(
  root = tempdir(),
  train = TRUE,
  transform = NULL,
  target_transform = NULL,
  download = FALSE
)

Arguments

root	(string, optional): Root directory for dataset storage, the dataset will be stored under root/fer2013.
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.

Details

The dataset is split into:

• "Train": training images labeled as "Training" in the original CSV.

• "Test": includes both "PublicTest" and "PrivateTest" entries.

Value

A torch dataset of class fer_dataset. Each element is a named list:

• x: a 48x48 grayscale array

• y: an integer from 1 to 7 indicating the class index

See Also

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

Examples

## Not run: 
fer <- fer_dataset(train = TRUE, download = TRUE)
first_item <- fer[1]
first_item$x  # 48x48 grayscale array
first_item$y  # 4
fer$classes[first_item$y]  # "Happy"

## End(Not run)

torchvision documentation built on Aug. 8, 2025, 7:27 p.m.