Datasets:
File size: 3,805 Bytes
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license: other
pretty_name: OpenPSS (community mirror)
tags:
- page-stream-segmentation
- document-ai
- document-boundary-detection
- benchmark
- mirror
task_categories:
- image-classification
dataset_info:
- config_name: LONG
features:
- name: stream_id
dtype: string
- name: position
dtype: int32
- name: image
dtype: image
- name: text
dtype: string
- name: label
dtype: int8
splits:
- name: train
num_bytes: 998698445
num_examples: 63815
- name: test
num_bytes: 405971545
num_examples: 25676
download_size: 1334166455
dataset_size: 1404669990
- config_name: SHORT
features:
- name: stream_id
dtype: string
- name: position
dtype: int32
- name: image
dtype: image
- name: text
dtype: string
- name: label
dtype: int8
splits:
- name: train
num_bytes: 976671526
num_examples: 40715
- name: test
num_bytes: 293561622
num_examples: 11462
download_size: 1224066290
dataset_size: 1270233148
configs:
- config_name: LONG
data_files:
- split: train
path: LONG/train-*
- split: test
path: LONG/test-*
- config_name: SHORT
data_files:
- split: train
path: SHORT/train-*
- split: test
path: SHORT/test-*
---
# OpenPSS — community mirror
> ⚠️ **This is a redistribution (mirror) of the OpenPSS benchmark, not our own work.** It is hosted for
> availability and reproducibility. **All credit belongs to the original authors.** If you are an author or
> rights-holder and would like any change or removal, please open a discussion here or contact us.
## Original work
**OpenPSS: An Open Page Stream Segmentation Benchmark** — Ruben van Heusden, Jaap Kamps, Maarten Marx
(University of Amsterdam, IRLab), *TPDL 2024* (DOI [10.1007/978-3-031-72437-4_24](https://link.springer.com/chapter/10.1007/978-3-031-72437-4_24)).
Builds on **WooIR** (van Heusden, Kamps, Marx, *SIGIR ICTIR 2022*).
## What this is
**Page Stream Segmentation (PSS):** given a stream of concatenated scanned pages, recover the original
document boundaries. OpenPSS provides two datasets — **SHORT** and **LONG**. The source documents are
Dutch government records released under the Freedom of Information Act (*Wet open overheid* / Woo), which
are public records.
This is a **self-contained, HuggingFace-native reformatting** of the original OpenPSS release (page images
embedded — no external `png.zip` to unpack), exposed as two loadable **configs** with train/test splits:
```python
from datasets import load_dataset
short = load_dataset("nutrientdocs/openpss-mirror", "SHORT") # or "LONG"
# columns: stream_id (str), position (int, 1-indexed page in the stream),
# image (PIL), text (OCR), label (int: 1 = starts a new document / boundary, else 0)
```
A stream's ground-truth boundaries are the `label` column ordered by `position`; `label[0]` (page 1) is 1
by construction. Content is faithful to the original OpenPSS SHORT/LONG; only the packaging is changed.
## Citation
```bibtex
@inproceedings{vanHeusden2024OpenPSS,
title = {OpenPSS: An Open Page Stream Segmentation Benchmark},
author = {van Heusden, Ruben and Kamps, Jaap and Marx, Maarten},
booktitle = {Theory and Practice of Digital Libraries (TPDL)},
year = {2024}, doi = {10.1007/978-3-031-72437-4_24}
}
```
## License / terms
The underlying documents are Dutch FOIA (Woo) **public records**; OpenPSS is distributed as an open
benchmark. This mirror redistributes the material under those terms — please consult the original
publication for authoritative licensing. Attribution to the original authors is required.
*Mirror maintained by Nutrient (`nutrientdocs`) to keep the OpenPSS benchmark reliably available and to make
our page-stream-segmentation results reproducible.*
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