metadata

pretty_name: DanishWIT
language:
  - da
license:
  - cc-by-sa-4.0
size_categories:
  - 100K<n<1M
source_datasets:
  - wikimedia/wit_base
task_categories:
  - image-to-text
task_ids:
  - image-captioning

Dataset Card for Danish WIT

Dataset Summary

Google presented the Wikipedia Image Text (WIT) dataset in July 2021, a dataset which contains scraped images from Wikipedia along with their descriptions. WikiMedia released WIT-Base in September 2021, being a modified version of WIT where they have removed the images with empty "reference descriptions", as well as removing images where a person's face covers more than 10% of the image surface, along with inappropriate images that are candidate for deletion. This dataset is the Danish portion of the WIT-Base dataset, consisting of roughly 160,000 images with associated Danish descriptions. We release the dataset under the CC BY-SA 4.0 license, in accordance with WIT-Base's identical license.

Supported Tasks and Leaderboards

Training machine learning models for caption generation, zero-shot image classification and text-image search are the intended tasks for this dataset. No leaderboard is active at this point.

Languages

The dataset is available in Danish (da).

Dataset Structure

Data Instances

Size of downloaded dataset files: 7.5 GB
Size of the generated dataset: 7.8 GB
Total amount of disk used: 15.3 GB

An example from the train split looks as follows.

{
    "image": {
        "bytes": b"\xff\xd8\xff\xe0\x00\x10JFIF...",
        "path": None
    },
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/4/45/Bispen_-_inside.jpg",
    "embedding": [2.8568285, 2.9562542, 0.33794892, 8.753725, ...],
    "metadata_url": "http://commons.wikimedia.org/wiki/File:Bispen_-_inside.jpg",
    "original_height": 3161,
    "original_width": 2316,
    "mime_type": "image/jpeg",
    "caption_attribution_description": "Kulturhuset Bispen set indefra. Biblioteket er til venstre",
    "page_url": "https://da.wikipedia.org/wiki/Bispen",
    "attribution_passes_lang_id": True,
    "caption_alt_text_description": None,
    "caption_reference_description": "Bispen set indefra fra 1. sal, hvor ....",
    "caption_title_and_reference_description": "Bispen [SEP] Bispen set indefra ...",
    "context_page_description": "Bispen er navnet på det offentlige kulturhus i ...",
    "context_section_description": "Bispen er navnet på det offentlige kulturhus i ...",
    "hierarchical_section_title": "Bispen",
    "is_main_image": True,
    "page_changed_recently": True,
    "page_title": "Bispen",
    "section_title": None
}

Data Fields

The data fields are the same among all splits.

image: a dict feature.
image_url: a str feature.
embedding: a list feature.
metadata_url: a str feature.
original_height: an int or NaN feature.
original_width: an int or NaN feature.
mime_type: a str or None feature.
caption_attribution_description: a str or None feature.
page_url: a str feature.
attribution_passes_lang_id: a bool or None feature.
caption_alt_text_description: a str or None feature.
caption_reference_description: a str or None feature.
caption_title_and_reference_description: a str or None feature.
context_page_description: a str or None feature.
context_section_description: a str or None feature.
hierarchical_section_title: a str feature.
is_main_image: a bool or None feature.
page_changed_recently: a bool or None feature.
page_title: a str feature.
section_title: a str or None feature.

Data Splits

Roughly 2.60% of the WIT-Base dataset comes from the Danish Wikipedia. We have split the resulting 168,740 samples into a training set, validation set and testing set of the following sizes:

split	samples
train	167,460
val	256
test	1,024

Dataset Creation

Curation Rationale

It is quite cumbersome to extract the Danish portion of the WIT-Base dataset, especially as the dataset takes up 333 GB of disk space, so the curation of Danish-WIT is purely to make it easier to work with the Danish portion of it.

Source Data

The original data was collected from WikiMedia's WIT-Base dataset, which in turn comes from Google's WIT dataset.

Datasets:

severo
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danish-wit