license:other region:us
---
license: other
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': cheese_plate
          '17': cheesecake
          '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: 3823897663.06
    num_examples: 75284
  - name: test
    num_bytes: 1271132919.55
    num_examples: 25150
  download_size: 5037088300
  dataset_size: 5095030582.61
---

# Description

The vl-food101 dataset by [Visual Layer](https://visual-layer.com) is a sanitized version of the original [Food101](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/) dataset. 
This dataset consists of 101 food categories with about 101,000 images in total.

The following are issues found in the original dataset and removed in this dataset:

<table>
    <thead>
        <tr>
            <th style="text-align: left;">Category</th>
            <th style="text-align: left;">Percentage</th>
            <th style="text-align: left;">Count</th>
        </tr>
    </thead>
    <tbody>
        <tr>
            <td style="text-align: left;">Duplicates</td>
            <td style="text-align: left;"><div>0.23%</div></td>
            <td style="text-align: left;"><div>235</div></td>
        </tr>
        <tr>
            <td style="text-align: left;">Outliers</td>
            <td style="text-align: left;"><div>0.08%</div></td>
            <td style="text-align: left;"><div>77</div></td>
        </tr>
        <tr>
            <td style="text-align: left;">Blur</td>
            <td style="text-align: left;"><div>0.18%</div></td>
            <td style="text-align: left;"><div>185</div></td>
        </tr>
        <tr>
            <td style="text-align: left;">Dark</td>
            <td style="text-align: left;"><div>0.04%</div></td>
            <td style="text-align: left;"><div>43</div></td>
        </tr>
        <tr>
            <td style="text-align: left;">Leakage</td>
            <td style="text-align: left;"><div>0.086%</div></td>
            <td style="text-align: left;"><div>87</div></td>
        </tr>
        <tr>
            <td style="text-align: left; font-weight: bold;">Total</td>
            <td style="text-align: left; font-weight: bold;"><div>0.62%</div></td>
            <td style="text-align: left; font-weight: bold;"><div>627</div></td>
        </tr>
    </tbody>
</table>


Learn more - https://docs.visual-layer.com/docs/available-datasets#vl-food101


# About Visual-Layer

<div align="center">
<a href="https://www.visual-layer.com">
  <img alt="Visual Layer Logo" src="https://github.com/visual-layer/visuallayer/blob/main/imgs/vl_horizontal_logo.png?raw=true" alt="Logo" width="400">
</a>
</div>


Visual Layer is founded by the authors of [XGBoost](https://github.com/apache/tvm), [Apache TVM](https://github.com/apache/tvm) & [Turi Create](https://github.com/apple/turicreate) - [Danny Bickson](https://www.linkedin.com/in/dr-danny-bickson-835b32), [Carlos Guestrin](https://www.linkedin.com/in/carlos-guestrin-5352a869) and [Amir Alush](https://www.linkedin.com/in/amiralush).

Learn more about Visual Layer [here](https://visual-layer.com).