`datasets`

function defined in module FastAI.Registries


			datasets(; filters...)

Show a registry of available datasets. Pass in filters as keyword arguments to look at a subset.

See also finding functionality, learningtasks, and datarecipes. For more information on registries, see FeatureRegistries.jl .

Examples

Show all available learning tasks:


			
			
			
			using
			
			 

	
			FastAI
			

			

			datasets
			(
			)

Datasets
ID	Description	Size	Tags	Package	Is downloaded	Dataset loader
:id	:description	:size	:tags	:package	:downloaded	:loader
"CUB_200_2011"	missing	1GiB	String[]	`FastAI`	false	type_format
"bedroom"	missing	4.25GiB	String[]	`FastAI`	false	type_format
"caltech_101"	missing	126MiB	String[]	`FastAI`	false	type_format
"cifar10"	missing	missing	String[]	`FastAI`	false	type_format
"cifar100"	missing	missing	String[]	`FastAI`	false	type_format
"food-101"	101 food categories, with 101,000 images; 250 test images and 750 training images per class. The training images were not cleaned. All images were rescaled to have a maximum side length of 512 pixels.	5.3GB	String[]	`FastAI`	false	type_format
"imagenette-160"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	1.45GiB	String[]	`FastAI`	false	type_format
"imagenette-320"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2-160"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2-320"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagewang-160"	missing	182MiB	String[]	`FastAI`	false	type_format
"imagewang-320"	missing	639MiB	String[]	`FastAI`	false	type_format
"imagewang"	missing	missing	String[]	`FastAI`	false	type_format
"imagewoof-160"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof-320"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof2-160"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof2-320"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	313MB	String[]	`FastAI`	false	type_format
"imagewoof2"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	1.25GiB	String[]	`FastAI`	false	type_format
"mnist_png"	missing	missing	String[]	`FastAI`	false	type_format
"mnist_var_size_tiny"	missing	missing	String[]	`FastAI`	false	type_format
"oxford-102-flowers"	missing	missing	String[]	`FastAI`	false	type_format
"oxford-iiit-pet"	missing	missing	String[]	`FastAI`	false	type_format
"stanford-cars"	missing	missing	String[]	`FastAI`	false	type_format
"ag_news_csv"	missing	11MB	String[]	`FastAI`	false	type_format
"amazon_review_full_csv"	missing	600MB	String[]	`FastAI`	false	type_format
"amazon_review_polarity_csv"	missing	600MB	String[]	`FastAI`	false	type_format
"dbpedia_csv"	missing	65MB	String[]	`FastAI`	false	type_format
"giga-fren"	missing	2.4GB	String[]	`FastAI`	false	type_format
"imdb"	missing	140MB	String[]	`FastAI`	false	type_format
"sogou_news_csv"	missing	360MB	String[]	`FastAI`	false	type_format
"wikitext-103"	missing	181MB	String[]	`FastAI`	false	type_format
"wikitext-2"	missing	4MB	String[]	`FastAI`	false	type_format
"yahoo_answers_csv"	missing	305MB	String[]	`FastAI`	false	type_format
"yelp_review_full_csv"	missing	187MB	String[]	`FastAI`	false	type_format
"yelp_review_polarity_csv"	missing	158MB	String[]	`FastAI`	false	type_format
"biwi_head_pose"	missing	430MiB	String[]	`FastAI`	false	type_format
"camvid"	missing	571MB	String[]	`FastAI`	false	type_format
"pascal-voc"	missing	4.3GB	String[]	`FastAI`	false	type_format
"pascal_2007"	missing	missing	String[]	`FastAI`	false	type_format
"pascal_2012"	missing	missing	String[]	`FastAI`	false	type_format
"siim_small"	missing	missing	String[]	`FastAI`	false	type_format
"skin-lesion"	missing	missing	String[]	`FastAI`	false	type_format
"tcga-small"	missing	missing	String[]	`FastAI`	false	type_format
"adult_sample"	missing	3.8MB	String[]	`FastAI`	false	type_format
"biwi_sample"	missing	missing	String[]	`FastAI`	false	type_format
"camvid_tiny"	missing	missing	String[]	`FastAI`	false	type_format
"dogscats"	missing	800MiB	String[]	`FastAI`	false	type_format
"human_numbers"	missing	missing	String[]	`FastAI`	false	type_format
"imdb_sample"	missing	4KB	String[]	`FastAI`	false	type_format
"mnist_sample"	missing	3MB	String[]	`FastAI`	false	type_format
"mnist_tiny"	missing	300KB	String[]	`FastAI`	false	type_format
"movie_lens_sample"	missing	missing	String[]	`FastAI`	false	type_format
"planet_sample"	missing	14.8MB	String[]	`FastAI`	false	type_format
"planet_tiny"	missing	1MB	String[]	`FastAI`	false	type_format
"coco_sample"	missing	3GB	String[]	`FastAI`	false	type_format
"coco-train2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-val2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-test2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-unlabeled2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-image_info_test2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-image_info_unlabeled2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-annotations_trainval2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-stuff_annotations_trainval2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-panoptic_annotations_trainval2017"	missing	missing	String[]	`FastAI`	false	type_format
"ecg5000"	The original dataset for "ECG5000" is a 20-hour long ECG downloaded from Physionet. The name is BIDMC Congestive Heart Failure Database(chfdb) and it is record "chf07".	10MB	String[]	`FastAI`	false	type_format
"atrial"	This is a physionet dataset of two-channel ECG recordings has been created from data used in the Computers in Cardiology Challenge 2004, an open competition with the goal of developing automated methods for predicting spontaneous termination of atrial fibrillation (AF).	226KB	String[]	`FastAI`	false	type_format
"natops"	The data is generated by sensors on the hands, elbows, wrists and thumbs. The data are the x,y,z coordinates for each of the eight locations.	5.1MB	String[]	`FastAI`	false	type_format
"appliances_energy"	The goal of this dataset is to predict total energy usage in kWh of a house.	15MB	String[]	`FastAI`	false	type_format

Download a dataset:


			
			
			
			path
			 
			=
			 
			
			load
			(
			
			

			datasets
			(
			)
			[
			
			"
			imagenette2-160
			"
			]
			)


			/home/runner/.julia/datadeps/fastai-imagenette2-160

Get an explanation of fields in the dataset registry:


			
			
			
			info
			(
			

			datasets
			(
			)
			)


			Information on registry Datasets

Fields: 
  Name             Column         Type                            Description                                                                                                 
  ID               :id (ID)       String                       
  Description      :description   String                          More information about the dataset
  Size             :size          String                          Download size of the dataset
  Tags             :tags          Vector{String}               
  Package          :package       Module                       
  Is downloaded    :downloaded    Bool                                Whether the dataset has been downloaded and is available locally.\n    Updates after session restart.\n
  Dataset loader   :loader        FastAI.Datasets.DatasetLoader

Description: 
A registry for datasets. loading an entry will download a dataset (if it
  hasn't been already), and return a path to where the files were downloaded.

  path = load(datasets()[id])

  See datarecipes to load these datasets in a format compatible with learning
  tasks.

Show all datasets with "image" in their name:


			
			
			

			datasets
			(
			
			id
			=
			
			"
			image
			"
			)

Datasets
ID	Description	Size	Tags	Package	Is downloaded	Dataset loader
:id	:description	:size	:tags	:package	:downloaded	:loader
"imagenette-160"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	1.45GiB	String[]	`FastAI`	false	type_format
"imagenette-320"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2-160"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2-320"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagenette2"	A subset of 10 easily classified classes from Imagenet: tench, English springer, cassette player, chain saw, church, French horn, garbage truck, gas pump, golf ball, parachute	missing	String[]	`FastAI`	false	type_format
"imagewang-160"	missing	182MiB	String[]	`FastAI`	false	type_format
"imagewang-320"	missing	639MiB	String[]	`FastAI`	false	type_format
"imagewang"	missing	missing	String[]	`FastAI`	false	type_format
"imagewoof-160"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof-320"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof2-160"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	missing	String[]	`FastAI`	false	type_format
"imagewoof2-320"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	313MB	String[]	`FastAI`	false	type_format
"imagewoof2"	A subset of 10 harder to classify classes from Imagenet (all dog breeds): Australian terrier, Border terrier, Samoyed, beagle, Shih-Tzu, English foxhound, Rhodesian ridgeback, dingo, golden retriever, Old English sheepdog	1.25GiB	String[]	`FastAI`	false	type_format
"coco-image_info_test2017"	missing	missing	String[]	`FastAI`	false	type_format
"coco-image_info_unlabeled2017"	missing	missing	String[]	`FastAI`	false	type_format

Methods

There is 1 method for FastAI.Registries.datasets:

Registries/datasets.jl:107

Backlinks

The following pages link back here:

Blocks and encodings, Custom learning tasks, Data containers, Discovery, Feature registries in FastAI.jl, How to find functionality, How to visualize data, Image segmentation, Keypoint regression, Presizing vision datasets for performance, Saving and loading models for inference, Siamese image similarity, Tabular Classification, Variational autoencoders, fastai API comparison

Registries/Registries.jl , Registries/datasets.jl