metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': az
            '1': be
            '2': en
            '3': et
            '4': fn
            '5': gr
            '6': ja
            '7': kk
            '8': ko
            '9': lt
            '10': lv
            '11': mn
            '12': 'no'
            '13': pl
            '14': ru
            '15': uk
            '16': zh
  splits:
    - name: train
      num_bytes: 7057770706.296
      num_examples: 2006
    - name: test
      num_bytes: 1246282602
      num_examples: 339
  download_size: 7700053691
  dataset_size: 8304053308.296
task_categories:
  - text-classification
  - translation
  - feature-extraction
tags:
  - code
size_categories:
  - 1K<n<10K
license: mit
language:
  - az
  - be
  - en
  - et
  - fi
  - ka
  - ja
  - ko
  - kk
  - lv
  - lt
  - mn
  - 'no'
  - pl
  - ru
  - uk
  - zh
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

Dataset Card for "docs_on_several_languages"

This dataset is a collection of different images in different languages. The daset includes the following languages: Azerbaijani (az: 0), Belorussian (be: 1), Chinese (zh: 16), English (en: 2), Estonian (et: 3), Finnish (fn: 4), Georgian (gr: 5), Japanese (ja: 6), Korean (ko: 7), Kazakh (kk: 8), Latvian (lv: 10), Lithuanian (lt: 9), Mongolian (mn: 11), Norwegian (no: 12), Polish (pl: 13), Russian (ru: 14), Ukranian (uk: 15). Each language has a corresponding class label defined. At least 100 images in the entire dataset are allocated per class. This dataset was originally used for the task of classifying the language of a document based on its image, but I hope it can help you in other machine learning tasks.