datarecipes
function
defined in module
FastAI.Registries
datarecipes(; filters...)
Show a registry of available dataset recipes. A dataset recipe defines how to load a dataset into a suitable format for use with a learning task.
Pass in filters as keyword arguments to look at a subset.
See also
finding functionality,
datasets
, and
learningtasks
. For more information on registries, see
FeatureRegistries.jl
.
Show all available dataset recipes:
using
FastAI
datarecipes
(
)
ID | Block types | Description | Is downloaded | Dataset ID | Package | Recipe |
---|---|---|---|---|---|---|
:id | :blocks | :description | :downloaded | :datasetid | :package | :recipe |
"CUB_200_2011" |
|
missing | false | CUB_200_2011 | FastVision | ImageFolders |
"imagenette" |
|
missing | false | imagenette | FastVision | ImageFolders |
"imagenette2" |
|
missing | false | imagenette2 | FastVision | ImageFolders |
"imagewang-320" |
|
missing | false | imagewang-320 | FastVision | ImageFolders |
"mnist_sample" |
|
missing | false | mnist_sample | FastVision | ImageFolders |
"pascal_2007" |
|
missing | false | pascal_2007 | FastVision | ImageTableMultiLabel |
"camvid" |
|
missing | false | camvid | FastVision | ImageSegmentationFolders |
"camvid_tiny" |
|
missing | false | camvid_tiny | FastVision | ImageSegmentationFolders |
"imagenette-160" |
|
missing | false | imagenette-160 | FastVision | ImageFolders |
"imagenette-320" |
|
missing | false | imagenette-320 | FastVision | ImageFolders |
"imagewoof2-160" |
|
missing | false | imagewoof2-160 | FastVision | ImageFolders |
"cifar100" |
|
missing | false | cifar100 | FastVision | ImageFolders |
"imagewang-160" |
|
missing | false | imagewang-160 | FastVision | ImageFolders |
"mnist_var_size_tiny" |
|
missing | false | mnist_var_size_tiny | FastVision | ImageFolders |
"cifar10" |
|
missing | false | cifar10 | FastVision | ImageFolders |
"mnist_png" |
|
missing | false | mnist_png | FastVision | ImageFolders |
"caltech_101" |
|
missing | false | caltech_101 | FastVision | ImageFolders |
"food-101" |
|
missing | false | food-101 | FastVision | ImageFolders |
"imagenette2-320" |
|
missing | false | imagenette2-320 | FastVision | ImageFolders |
"imagewoof2" |
|
missing | false | imagewoof2 | FastVision | ImageFolders |
"imagewoof2-320" |
|
missing | false | imagewoof2-320 | FastVision | ImageFolders |
"imagewoof-160" |
|
missing | false | imagewoof-160 | FastVision | ImageFolders |
"imagewoof-320" |
|
missing | false | imagewoof-320 | FastVision | ImageFolders |
"imagewang" |
|
missing | false | imagewang | FastVision | ImageFolders |
"mnist_tiny" |
|
missing | false | mnist_tiny | FastVision | ImageFolders |
"imagewoof" |
|
missing | false | imagewoof | FastVision | ImageFolders |
"imagenette2-160" |
|
missing | false | imagenette2-160 | FastVision | ImageFolders |
"adult_sample" |
|
missing | false | adult_sample | FastTabular | TableDatasetRecipe |
"adult_sample/clf_salary" |
|
missing | false | adult_sample | FastTabular | TableClassificationRecipe |
"adult_sample/reg_age" |
|
missing | false | adult_sample | FastTabular | TableRegressionRecipe |
"imdb_sample" |
|
missing | false | imdb_sample | FastTabular | TableDatasetRecipe |
"imdb_sample/clf" |
|
missing | false | imdb_sample | FastTabular | TableClassificationRecipe |
Show all recipes for datasets that have "image" in their name:
datarecipes
(
datasetid
=
"
image
"
)
ID | Block types | Description | Is downloaded | Dataset ID | Package | Recipe |
---|---|---|---|---|---|---|
:id | :blocks | :description | :downloaded | :datasetid | :package | :recipe |
"imagenette" |
|
missing | false | imagenette | FastVision | ImageFolders |
"imagenette2" |
|
missing | false | imagenette2 | FastVision | ImageFolders |
"imagewang-320" |
|
missing | false | imagewang-320 | FastVision | ImageFolders |
"imagenette-160" |
|
missing | false | imagenette-160 | FastVision | ImageFolders |
"imagenette-320" |
|
missing | false | imagenette-320 | FastVision | ImageFolders |
"imagewoof2-160" |
|
missing | false | imagewoof2-160 | FastVision | ImageFolders |
"imagewang-160" |
|
missing | false | imagewang-160 | FastVision | ImageFolders |
"imagenette2-320" |
|
missing | false | imagenette2-320 | FastVision | ImageFolders |
"imagewoof2" |
|
missing | false | imagewoof2 | FastVision | ImageFolders |
"imagewoof2-320" |
|
missing | false | imagewoof2-320 | FastVision | ImageFolders |
"imagewoof-160" |
|
missing | false | imagewoof-160 | FastVision | ImageFolders |
"imagewoof-320" |
|
missing | false | imagewoof-320 | FastVision | ImageFolders |
"imagewang" |
|
missing | false | imagewang | FastVision | ImageFolders |
"imagewoof" |
|
missing | false | imagewoof | FastVision | ImageFolders |
"imagenette2-160" |
|
missing | false | imagenette2-160 | FastVision | ImageFolders |
Show all data recipes usable for classification tasks, that is where the target block is a
Label
:
datarecipes
(
blocks
=
(
Any
,
Label
)
)
ID | Block types | Description | Is downloaded | Dataset ID | Package | Recipe |
---|---|---|---|---|---|---|
:id | :blocks | :description | :downloaded | :datasetid | :package | :recipe |
"CUB_200_2011" |
|
missing | false | CUB_200_2011 | FastVision | ImageFolders |
"imagenette" |
|
missing | false | imagenette | FastVision | ImageFolders |
"imagenette2" |
|
missing | false | imagenette2 | FastVision | ImageFolders |
"imagewang-320" |
|
missing | false | imagewang-320 | FastVision | ImageFolders |
"mnist_sample" |
|
missing | false | mnist_sample | FastVision | ImageFolders |
"imagenette-160" |
|
missing | false | imagenette-160 | FastVision | ImageFolders |
"imagenette-320" |
|
missing | false | imagenette-320 | FastVision | ImageFolders |
"imagewoof2-160" |
|
missing | false | imagewoof2-160 | FastVision | ImageFolders |
"cifar100" |
|
missing | false | cifar100 | FastVision | ImageFolders |
"imagewang-160" |
|
missing | false | imagewang-160 | FastVision | ImageFolders |
"mnist_var_size_tiny" |
|
missing | false | mnist_var_size_tiny | FastVision | ImageFolders |
"cifar10" |
|
missing | false | cifar10 | FastVision | ImageFolders |
"mnist_png" |
|
missing | false | mnist_png | FastVision | ImageFolders |
"caltech_101" |
|
missing | false | caltech_101 | FastVision | ImageFolders |
"food-101" |
|
missing | false | food-101 | FastVision | ImageFolders |
"imagenette2-320" |
|
missing | false | imagenette2-320 | FastVision | ImageFolders |
"imagewoof2" |
|
missing | false | imagewoof2 | FastVision | ImageFolders |
"imagewoof2-320" |
|
missing | false | imagewoof2-320 | FastVision | ImageFolders |
"imagewoof-160" |
|
missing | false | imagewoof-160 | FastVision | ImageFolders |
"imagewoof-320" |
|
missing | false | imagewoof-320 | FastVision | ImageFolders |
"imagewang" |
|
missing | false | imagewang | FastVision | ImageFolders |
"mnist_tiny" |
|
missing | false | mnist_tiny | FastVision | ImageFolders |
"imagewoof" |
|
missing | false | imagewoof | FastVision | ImageFolders |
"imagenette2-160" |
|
missing | false | imagenette2-160 | FastVision | ImageFolders |
"adult_sample/clf_salary" |
|
missing | false | adult_sample | FastTabular | TableClassificationRecipe |
"imdb_sample/clf" |
|
missing | false | imdb_sample | FastTabular | TableClassificationRecipe |
Get an explanation of fields in the dataset recipe registry:
info
(
datarecipes
(
)
)
Information on registry Dataset recipes
Fields:
Name Column Type Description
ID :id (ID) String
Block types :blocks Any Types of blocks of the data container that this recipe loads.
Description :description String More information about the dataset recipe
Is downloaded :downloaded Bool Whether the dataset this recipe is based has been downloaded and is\n available locally.\n
Dataset ID :datasetid String ID of the dataset this recipe is based on.
Package :package Module
Recipe :recipe FastAI.Datasets.DatasetRecipe
Description:
A registry for dataset recipes. loading an entry will download the
corresponding dataset (see datasets) and return data, blocks, a data
container and the Blocks of the observations.
julia data, blocks = load(datarecipes()[id])
See learningtasks to find compatible learning tasks.
There is
1
method for FastAI.Registries.datarecipes
:
The following pages link back here:
Data containers, Discovery, FastAI.jl, Feature registries in FastAI.jl, How to augment vision data, How to find functionality, How to train a model, Introduction, Performant data pipelines, Quickstart, Text Classification, TimeSeries Classification, fastai API comparison, tsregression