Datasets:

alexandrainst
/

da-wit

	---
	pretty_name: Danish WIT
	language:
	- da
	license:
	- cc-by-sa-4.0
	size_categories:
	- 100K<n<1M
	source_datasets:
	- wikimedia/wit_base
	task_categories:
	- image-to-text
	- zero-shot-image-classification
	- feature-extraction
	task_ids:
	- image-captioning
	---

	# Dataset Card for Danish WIT

	## Dataset Description

	- Repository: <https://gist.github.com/saattrupdan/bb6c9c52d9f4b35258db2b2456d31224>
	- Point of Contact: [Dan Saattrup Nielsen](mailto:dan.nielsen@alexandra.dk)
	- Size of downloaded dataset files: 7.5 GB
	- Size of the generated dataset: 7.8 GB
	- Total amount of disk used: 15.3 GB

	### Dataset Summary

	Google presented the Wikipedia Image Text (WIT) dataset in [July
	2021](https://dl.acm.org/doi/abs/10.1145/3404835.3463257), a dataset which contains
	scraped images from Wikipedia along with their descriptions. WikiMedia released
	WIT-Base in [September
	2021](https://techblog.wikimedia.org/2021/09/09/the-wikipedia-image-caption-matching-challenge-and-a-huge-release-of-image-data-for-research/),
	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](https://creativecommons.org/licenses/by-sa/4.0/), in
	accordance with WIT-Base's [identical
	license](https://huggingface.co/datasets/wikimedia/wit_base#licensing-information).


	### 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": [PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=300x409 at 0x7FE4384E2190],
	"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`: an `Image` 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](https://huggingface.co/datasets/wikimedia/wit_base) dataset, which in turn
	comes from Google's [WIT](https://huggingface.co/datasets/google/wit) dataset.


	## Additional Information

	### Dataset Curators

	[Dan Saattrup Nielsen](https://saattrupdan.github.io/) from the [The Alexandra
	Institute](https://alexandra.dk/) curated this dataset.

	### Licensing Information

	The dataset is licensed under the [CC BY-SA 4.0
	license](https://creativecommons.org/licenses/by-sa/4.0/).