fer_dataset {torchvision} | R Documentation |
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 |
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 |
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)