Subset of the famous ImageNet dataset.
The data is obtained from torchvision::tiny_imagenet_dataset().
The underlying DataBackend contains columns "class", "image", "..row_id", "split", where the last column
indicates whether the row belongs to the train, validation or test set that defined provided in torchvision.
There are no labels for the test rows, so by default, these observations are inactive, which means that the task uses only 110000 of the 120000 observations that are defined in the underlying data backend.
Download
The task's backend is a DataBackendLazy which will download the data once it is requested.
Other meta-data is already available before that.
You can cache these datasets by setting the mlr3torch.cache option to TRUE or to a specific path to be used
as the cache directory.
Properties
Task type: “classif”
Properties: “multiclass”
Has Missings: no
Target: “class”
Features: “image”
Data Dimension: 120000x4
References
Deng, Jia, Dong, Wei, Socher, Richard, Li, Li-Jia, Li, Kai, Fei-Fei, Li (2009). “Imagenet: A large-scale hierarchical image database.” In 2009 IEEE conference on computer vision and pattern recognition, 248–255. IEEE.
Examples
task = tsk("tiny_imagenet")
task
#> <TaskClassif:tiny_imagenet> (110000 x 2): ImageNet Subset
#> * Target: class
#> * Properties: multiclass
#> * Features (1):
#> - lt (1): image