oxfordiiitpet_dataset: Oxford-IIIT Pet Classification Datasets

In torchvision: Models, Datasets and Transformations for Images

Oxford-IIIT Pet Classification Datasets

Description

Oxford-IIIT Pet Datasets

Usage

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

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

Arguments

root	Character. Root directory where the dataset is stored or will be downloaded to. Files are placed under root/oxfordiiitpet.
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 Oxford-IIIT Pet collection is a classification dataset consisting of high-quality images of 37 cat and dog breeds. It includes two variants:

• oxfordiiitpet_dataset: Multi-class classification across 37 pet breeds.

• oxfordiiitpet_binary_dataset: Binary classification distinguishing cats vs dogs.

The Oxford-IIIT Pet dataset contains over 7,000 images across 37 categories, with roughly 200 images per class. Each image is labeled with its breed and species (cat/dog).

Value

A torch dataset object oxfordiiitpet_dataset or oxfordiiitpet_binary_dataset. Each element is a named list with:

• x: A H x W x 3 integer array representing an RGB image.

• y: An integer label:

  • For oxfordiiitpet_dataset: a value from 1–37 representing the breed.

  • For oxfordiiitpet_binary_dataset: 1 for Cat, 2 for Dog.

See Also

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

Examples

## Not run: 
# Multi-class version
oxford <- oxfordiiitpet_dataset(download = TRUE)
first_item <- oxford[1]
first_item$x  # RGB image
first_item$y  # Label in 1–37
oxford$classes[first_item$y]  # Breed name

# Binary version
oxford_bin <- oxfordiiitpet_binary_dataset(download = TRUE)
first_item <- oxford_bin[1]
first_item$x  # RGB image
first_item$y  # 1 for Cat, 2 for Dog
oxford_bin$classes[first_item$y]  # "Cat" or "Dog"

## End(Not run)

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