eurosat_dataset {torchvision} | R Documentation |
EuroSAT datasets
Description
A collection of Sentinel-2 satellite images for land-use classification. The standard version contains 27,000 RGB thumbnails (64x64) across 10 classes. Variants include the full 13 spectral bands and a small 100-image subset useful for demos.
Downloads and prepares the EuroSAT dataset with 13 spectral bands.
A subset of 100 images with 13 spectral bands useful for workshops and demos.
Usage
eurosat_dataset(
root = tempdir(),
split = "train",
download = FALSE,
transform = NULL,
target_transform = NULL
)
eurosat_all_bands_dataset(
root = tempdir(),
split = "train",
download = FALSE,
transform = NULL,
target_transform = NULL
)
eurosat100_dataset(
root = tempdir(),
split = "train",
download = FALSE,
transform = NULL,
target_transform = NULL
)
Arguments
root |
(Optional) Character. The root directory where the dataset will be stored.
if empty, will use the default |
split |
Character. Must be one of |
download |
Logical. If TRUE, downloads the dataset to |
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. |
Details
eurosat_dataset()
provides a total of 27,000 RGB labeled images.
eurosat_all_bands_dataset()
provides a total of 27,000 labeled images with 13 spectral channel bands.
eurosat100_dataset()
provides a subset of 100 labeled images with 13 spectral channel bands.
Value
A torch::dataset
object. Each item is a list with:
-
x
: a 64x64 image tensor with 3 (RGB) or 13 (all bands) channels -
y
: the class label
See Also
Other classification_dataset:
caltech_dataset
,
cifar10_dataset()
,
fer_dataset()
,
fgvc_aircraft_dataset()
,
flowers102_dataset()
,
mnist_dataset()
,
oxfordiiitpet_dataset()
,
tiny_imagenet_dataset()
Examples
## Not run:
# Initialize the dataset
ds <- eurosat100_dataset(split = "train", download = TRUE)
# Access the first item
head <- ds[1]
print(head$x) # Image
print(head$y) # Label
## End(Not run)