Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
100K - 1M
License:
metadata
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-foodspotting
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
paperswithcode_id: food-101
pretty_name: Food-101
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': apple_pie
'1': baby_back_ribs
'2': baklava
'3': beef_carpaccio
'4': beef_tartare
'5': beet_salad
'6': beignets
'7': bibimbap
'8': bread_pudding
'9': breakfast_burrito
'10': bruschetta
'11': caesar_salad
'12': cannoli
'13': caprese_salad
'14': carrot_cake
'15': ceviche
'16': cheesecake
'17': cheese_plate
'18': chicken_curry
'19': chicken_quesadilla
'20': chicken_wings
'21': chocolate_cake
'22': chocolate_mousse
'23': churros
'24': clam_chowder
'25': club_sandwich
'26': crab_cakes
'27': creme_brulee
'28': croque_madame
'29': cup_cakes
'30': deviled_eggs
'31': donuts
'32': dumplings
'33': edamame
'34': eggs_benedict
'35': escargots
'36': falafel
'37': filet_mignon
'38': fish_and_chips
'39': foie_gras
'40': french_fries
'41': french_onion_soup
'42': french_toast
'43': fried_calamari
'44': fried_rice
'45': frozen_yogurt
'46': garlic_bread
'47': gnocchi
'48': greek_salad
'49': grilled_cheese_sandwich
'50': grilled_salmon
'51': guacamole
'52': gyoza
'53': hamburger
'54': hot_and_sour_soup
'55': hot_dog
'56': huevos_rancheros
'57': hummus
'58': ice_cream
'59': lasagna
'60': lobster_bisque
'61': lobster_roll_sandwich
'62': macaroni_and_cheese
'63': macarons
'64': miso_soup
'65': mussels
'66': nachos
'67': omelette
'68': onion_rings
'69': oysters
'70': pad_thai
'71': paella
'72': pancakes
'73': panna_cotta
'74': peking_duck
'75': pho
'76': pizza
'77': pork_chop
'78': poutine
'79': prime_rib
'80': pulled_pork_sandwich
'81': ramen
'82': ravioli
'83': red_velvet_cake
'84': risotto
'85': samosa
'86': sashimi
'87': scallops
'88': seaweed_salad
'89': shrimp_and_grits
'90': spaghetti_bolognese
'91': spaghetti_carbonara
'92': spring_rolls
'93': steak
'94': strawberry_shortcake
'95': sushi
'96': tacos
'97': takoyaki
'98': tiramisu
'99': tuna_tartare
'100': waffles
splits:
- name: train
num_bytes: 3842657187
num_examples: 75750
- name: validation
num_bytes: 1275182340.5
num_examples: 25250
download_size: 5059972308
dataset_size: 5117839527.5
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
Dataset Description
- Homepage: Food-101 Dataset
- Repository:
- Paper: Paper
- Leaderboard:
- Point of Contact:
Dataset Summary
This dataset consists of 101 food categories, with 101'000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels.
Supported Tasks and Leaderboards
image-classification: The goal of this task is to classify a given image of a dish into one of 101 classes. The leaderboard is available here.
Languages
English
Data Instances
A sample from the training set is provided below:
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=384x512 at 0x276021C5EB8>,
'label': 23
}
Data Fields
The data instances have the following fields:
image: APIL.Image.Imageobject containing the image. Note that when accessing the image column:dataset[0]["image"]the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the"image"column, i.e.dataset[0]["image"]should always be preferred overdataset["image"][0].label: anintclassification label.
Class Label Mappings
{
"apple_pie": 0,
"baby_back_ribs": 1,
"baklava": 2,
"beef_carpaccio": 3,
"beef_tartare": 4,
"beet_salad": 5,
"beignets": 6,
"bibimbap": 7,
"bread_pudding": 8,
"breakfast_burrito": 9,
"bruschetta": 10,
"caesar_salad": 11,
"cannoli": 12,
"caprese_salad": 13,
"carrot_cake": 14,
"ceviche": 15,
"cheesecake": 16,
"cheese_plate": 17,
"chicken_curry": 18,
"chicken_quesadilla": 19,
"chicken_wings": 20,
"chocolate_cake": 21,
"chocolate_mousse": 22,
"churros": 23,
"clam_chowder": 24,
"club_sandwich": 25,
"crab_cakes": 26,
"creme_brulee": 27,
"croque_madame": 28,
"cup_cakes": 29,
"deviled_eggs": 30,
"donuts": 31,
"dumplings": 32,
"edamame": 33,
"eggs_benedict": 34,
"escargots": 35,
"falafel": 36,
"filet_mignon": 37,
"fish_and_chips": 38,
"foie_gras": 39,
"french_fries": 40,
"french_onion_soup": 41,
"french_toast": 42,
"fried_calamari": 43,
"fried_rice": 44,
"frozen_yogurt": 45,
"garlic_bread": 46,
"gnocchi": 47,
"greek_salad": 48,
"grilled_cheese_sandwich": 49,
"grilled_salmon": 50,
"guacamole": 51,
"gyoza": 52,
"hamburger": 53,
"hot_and_sour_soup": 54,
"hot_dog": 55,
"huevos_rancheros": 56,
"hummus": 57,
"ice_cream": 58,
"lasagna": 59,
"lobster_bisque": 60,
"lobster_roll_sandwich": 61,
"macaroni_and_cheese": 62,
"macarons": 63,
"miso_soup": 64,
"mussels": 65,
"nachos": 66,
"omelette": 67,
"onion_rings": 68,
"oysters": 69,
"pad_thai": 70,
"paella": 71,
"pancakes": 72,
"panna_cotta": 73,
"peking_duck": 74,
"pho": 75,
"pizza": 76,
"pork_chop": 77,
"poutine": 78,
"prime_rib": 79,
"pulled_pork_sandwich": 80,
"ramen": 81,
"ravioli": 82,
"red_velvet_cake": 83,
"risotto": 84,
"samosa": 85,
"sashimi": 86,
"scallops": 87,
"seaweed_salad": 88,
"shrimp_and_grits": 89,
"spaghetti_bolognese": 90,
"spaghetti_carbonara": 91,
"spring_rolls": 92,
"steak": 93,
"strawberry_shortcake": 94,
"sushi": 95,
"tacos": 96,
"takoyaki": 97,
"tiramisu": 98,
"tuna_tartare": 99,
"waffles": 100
}
Data Splits
| train | validation | |
|---|---|---|
| # of examples | 75750 | 25250 |