metadata

license: mit
dataset_info:
  features:
    - name: newspaper_name
      dtype: string
    - name: newspaper_arkindex_id
      dtype: string
    - name: page_arkindex_id
      dtype: string
    - name: page_index
      dtype: int64
    - name: page_image
      dtype: image
    - name: zone_arkindex_ids
      sequence: string
    - name: zone_polygons
      sequence:
        sequence:
          sequence: float64
    - name: zone_texts
      sequence: string
    - name: zone_classes
      sequence:
        class_label:
          names:
            '0': HEADER-TITLE
            '1': HEADER-TEXT
            '2': ARTICLE-ILLUSTRATION
            '3': ADVERTISEMENT
            '4': ANNOUNCEMENT
            '5': ARTICLE-TITLE
            '6': ARTICLE-TEXT
            '7': ARTICLE-SUBTITLE
            '8': ARTICLE-INSIDEHEADING
            '9': CAPTION
            '10': AUTHOR
            '11': ARTICLE-TABLE
            '12': SECTION-TITLE
    - name: zone_orders
      sequence: int64
    - name: article_id
      sequence: int64
  splits:
    - name: train
      num_bytes: 911036067
      num_examples: 623
    - name: val
      num_bytes: 75099123
      num_examples: 50
    - name: test
      num_bytes: 71901518
      num_examples: 48
  download_size: 1038604332
  dataset_size: 1058036708
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*

Newspaper segmentation dataset: Finlam

Dataset Description

Homepage: Finlam
Point of Contact: TEKLIA

Dataset Summary

The Finlam dataset includes 149 French newspapers from the 19th to 20th centuries.

Each newspaper contains multiple pages. Page images are resized to a fixed height of 2000 pixels.

Each page contains multiple zones, with different information such as polygon, text, class, and order.

Split

set	images	newspapers
train	623	129
val	50	10
test	48	10

Languages

Most newspapers in the dataset are French, some English.

Dataset Structure

Data Fields

newspaper_name: The name of the newspaper.
newspaper_arkindex_id: The Arkindex element id corresponding to the current newspaper.
page_arkindex_id: The Arkindex element id corresponding to the current page.
page_index: The index of the current page in the current newspaper.
page_image: a PIL.Image object containing the page image. Note that when accessing the image column (using dataset[0]["page_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]["page_image"] should always be preferred over dataset["page_image"][0].
zone_arkindex_ids: the list of Arkindex element ids corresponding to the zones in the page.
zone_polygons: the list of zone coordinates in the current page.
zone_texts: the list of zone texts in the current page.
zone_classes: the list of zone classes in the current page.
zone_orders: the list of zone indexes in the current page, defining the reading order.
article_id: the list of article indexes defining in which article in the current newspaper the current zone is located.