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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ annotations_creators:
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+ - crowdsourced
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+ language_creators:
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+ - crowdsourced
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+ language:
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+ - en
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+ license:
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+ - unknown
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - extended|other-foodspotting
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+ task_categories:
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+ - image-classification
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+ task_ids:
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+ - multi-class-image-classification
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+ paperswithcode_id: food-101
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+ pretty_name: Food-101
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+ dataset_info:
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+ features:
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+ - name: image
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+ dtype: image
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+ - name: label
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+ dtype:
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+ class_label:
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+ names:
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+ '0': apple_pie
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+ '1': baby_back_ribs
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+ '2': baklava
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+ '3': beef_carpaccio
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+ '4': beef_tartare
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+ '5': beet_salad
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+ '6': beignets
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+ '7': bibimbap
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+ '8': bread_pudding
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+ '9': breakfast_burrito
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+ '10': bruschetta
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+ '11': caesar_salad
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+ '12': cannoli
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+ '13': caprese_salad
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+ '14': carrot_cake
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+ '15': ceviche
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+ '16': cheesecake
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+ '17': cheese_plate
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+ '18': chicken_curry
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+ '19': chicken_quesadilla
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+ '20': chicken_wings
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+ '21': chocolate_cake
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+ '22': chocolate_mousse
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+ '23': churros
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+ '24': clam_chowder
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+ '25': club_sandwich
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+ '26': crab_cakes
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+ '27': creme_brulee
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+ '28': croque_madame
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+ '29': cup_cakes
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+ '30': deviled_eggs
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+ '31': donuts
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+ '32': dumplings
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+ '33': edamame
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+ '34': eggs_benedict
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+ '35': escargots
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+ '36': falafel
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+ '37': filet_mignon
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+ '38': fish_and_chips
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+ '39': foie_gras
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+ '40': french_fries
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+ '41': french_onion_soup
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+ '42': french_toast
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+ '43': fried_calamari
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+ '44': fried_rice
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+ '45': frozen_yogurt
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+ '46': garlic_bread
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+ '47': gnocchi
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+ '48': greek_salad
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+ '49': grilled_cheese_sandwich
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+ '50': grilled_salmon
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+ '51': guacamole
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+ '52': gyoza
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+ '53': hamburger
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+ '54': hot_and_sour_soup
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+ '55': hot_dog
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+ '56': huevos_rancheros
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+ '57': hummus
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+ '58': ice_cream
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+ '59': lasagna
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+ '60': lobster_bisque
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+ '61': lobster_roll_sandwich
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+ '62': macaroni_and_cheese
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+ '63': macarons
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+ '64': miso_soup
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+ '65': mussels
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+ '66': nachos
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+ '67': omelette
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+ '68': onion_rings
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+ '69': oysters
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+ '70': pad_thai
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+ '71': paella
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+ '72': pancakes
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+ '73': panna_cotta
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+ '74': peking_duck
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+ '75': pho
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+ '76': pizza
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+ '77': pork_chop
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+ '78': poutine
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+ '79': prime_rib
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+ '80': pulled_pork_sandwich
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+ '81': ramen
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+ '82': ravioli
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+ '83': red_velvet_cake
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+ '84': risotto
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+ '85': samosa
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+ '86': sashimi
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+ '87': scallops
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+ '88': seaweed_salad
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+ '89': shrimp_and_grits
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+ '90': spaghetti_bolognese
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+ '91': spaghetti_carbonara
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+ '92': spring_rolls
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+ '93': steak
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+ '94': strawberry_shortcake
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+ '95': sushi
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+ '96': tacos
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+ '97': takoyaki
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+ '98': tiramisu
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+ '99': tuna_tartare
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+ '100': waffles
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+ splits:
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+ - name: train
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+ num_bytes: 3842657187.0
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+ num_examples: 75750
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+ - name: validation
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+ num_bytes: 1275182340.5
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+ num_examples: 25250
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+ download_size: 5059972308
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+ dataset_size: 5117839527.5
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: validation
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+ path: data/validation-*
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+ ---
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [Food-101 Dataset](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/)
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+ - **Repository:**
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+ - **Paper:** [Paper](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/static/bossard_eccv14_food-101.pdf)
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+ - **Leaderboard:**
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+ - **Point of Contact:**
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+
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+ ### Dataset Summary
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+
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+ 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.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ - `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](https://paperswithcode.com/sota/fine-grained-image-classification-on-food-101).
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+
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+ ### Languages
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+
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+ English
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A sample from the training set is provided below:
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+
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+ ```
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+ {
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+ 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=384x512 at 0x276021C5EB8>,
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+ 'label': 23
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+ The data instances have the following fields:
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+
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+ - `image`: A `PIL.Image.Image` object 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 over `dataset["image"][0]`.
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+ - `label`: an `int` classification label.
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+
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+ <details>
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+ <summary>Class Label Mappings</summary>
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+
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+ ```json
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+ {
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+ "apple_pie": 0,
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+ "baby_back_ribs": 1,
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+ "baklava": 2,
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+ "beef_carpaccio": 3,
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+ "beef_tartare": 4,
199
+ "beet_salad": 5,
200
+ "beignets": 6,
201
+ "bibimbap": 7,
202
+ "bread_pudding": 8,
203
+ "breakfast_burrito": 9,
204
+ "bruschetta": 10,
205
+ "caesar_salad": 11,
206
+ "cannoli": 12,
207
+ "caprese_salad": 13,
208
+ "carrot_cake": 14,
209
+ "ceviche": 15,
210
+ "cheesecake": 16,
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+ "cheese_plate": 17,
212
+ "chicken_curry": 18,
213
+ "chicken_quesadilla": 19,
214
+ "chicken_wings": 20,
215
+ "chocolate_cake": 21,
216
+ "chocolate_mousse": 22,
217
+ "churros": 23,
218
+ "clam_chowder": 24,
219
+ "club_sandwich": 25,
220
+ "crab_cakes": 26,
221
+ "creme_brulee": 27,
222
+ "croque_madame": 28,
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+ "cup_cakes": 29,
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+ "deviled_eggs": 30,
225
+ "donuts": 31,
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+ "dumplings": 32,
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+ "edamame": 33,
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+ "eggs_benedict": 34,
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+ "escargots": 35,
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+ "falafel": 36,
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+ "filet_mignon": 37,
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+ "fish_and_chips": 38,
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+ "foie_gras": 39,
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+ "french_fries": 40,
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+ "french_onion_soup": 41,
236
+ "french_toast": 42,
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+ "fried_calamari": 43,
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+ "fried_rice": 44,
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+ "frozen_yogurt": 45,
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+ "garlic_bread": 46,
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+ "gnocchi": 47,
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+ "greek_salad": 48,
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+ "grilled_cheese_sandwich": 49,
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+ "grilled_salmon": 50,
245
+ "guacamole": 51,
246
+ "gyoza": 52,
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+ "hamburger": 53,
248
+ "hot_and_sour_soup": 54,
249
+ "hot_dog": 55,
250
+ "huevos_rancheros": 56,
251
+ "hummus": 57,
252
+ "ice_cream": 58,
253
+ "lasagna": 59,
254
+ "lobster_bisque": 60,
255
+ "lobster_roll_sandwich": 61,
256
+ "macaroni_and_cheese": 62,
257
+ "macarons": 63,
258
+ "miso_soup": 64,
259
+ "mussels": 65,
260
+ "nachos": 66,
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+ "omelette": 67,
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+ "onion_rings": 68,
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+ "oysters": 69,
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+ "pad_thai": 70,
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+ "paella": 71,
266
+ "pancakes": 72,
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+ "panna_cotta": 73,
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+ "peking_duck": 74,
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+ "pho": 75,
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+ "pizza": 76,
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+ "pork_chop": 77,
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+ "poutine": 78,
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+ "prime_rib": 79,
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+ "pulled_pork_sandwich": 80,
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+ "ramen": 81,
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+ "ravioli": 82,
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+ "red_velvet_cake": 83,
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+ "risotto": 84,
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+ "samosa": 85,
280
+ "sashimi": 86,
281
+ "scallops": 87,
282
+ "seaweed_salad": 88,
283
+ "shrimp_and_grits": 89,
284
+ "spaghetti_bolognese": 90,
285
+ "spaghetti_carbonara": 91,
286
+ "spring_rolls": 92,
287
+ "steak": 93,
288
+ "strawberry_shortcake": 94,
289
+ "sushi": 95,
290
+ "tacos": 96,
291
+ "takoyaki": 97,
292
+ "tiramisu": 98,
293
+ "tuna_tartare": 99,
294
+ "waffles": 100
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+ }
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+ ```
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+ </details>
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+
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+
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+ ### Data Splits
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+
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+
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+ | |train|validation|
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+ |----------|----:|---------:|
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+ |# of examples|75750|25250|