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---
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: 911036067.0
num_examples: 623
- name: val
num_bytes: 75099123.0
num_examples: 50
- name: test
num_bytes: 71901518.0
num_examples: 48
download_size: 1038604332
dataset_size: 1058036708.0
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](https://finlam.projets.litislab.fr/)
- **Point of Contact:** [TEKLIA](https://teklia.com)
## 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.
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