The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for "FUNSD"
Dataset Description
Dataset Summary
The FUNSD dataset, with one difference compared to the original dataset, each document image is resized to 224x224.
The FUNSD dataset is a collection of annotated forms.
This dataset loading script is taken from the official LayoutLMv2 implementation, and updated to not include any Detectron2 dependencies.
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
conll2000
- Size of downloaded dataset files: 3.32 MB
- Size of the generated dataset: 6.25 MB
- Total amount of disk used: 9.57 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"chunk_tags": [11, 13, 11, 12, 21, 22, 22, 22, 22, 11, 12, 12, 17, 11, 12, 13, 11, 0, 1, 13, 11, 11, 0, 21, 22, 22, 11, 12, 12, 13, 11, 12, 12, 11, 12, 12, 0],
"id": "0",
"pos_tags": [19, 14, 11, 19, 39, 27, 37, 32, 34, 11, 15, 19, 14, 19, 22, 14, 20, 5, 15, 14, 19, 19, 5, 34, 32, 34, 11, 15, 19, 14, 20, 9, 20, 24, 15, 22, 6],
"tokens": "[\"Confidence\", \"in\", \"the\", \"pound\", \"is\", \"widely\", \"expected\", \"to\", \"take\", \"another\", \"sharp\", \"dive\", \"if\", \"trade\", \"figur..."
}
Data Fields
The data fields are the same among all splits.
Data Splits
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@article{DBLP:journals/corr/abs-1905-13538,
author = {Guillaume Jaume and
Hazim Kemal Ekenel and
Jean{-}Philippe Thiran},
title = {{FUNSD:} {A} Dataset for Form Understanding in Noisy Scanned Documents},
journal = {CoRR},
volume = {abs/1905.13538},
year = {2019},
url = {http://arxiv.org/abs/1905.13538},
archivePrefix = {arXiv},
eprint = {1905.13538},
timestamp = {Mon, 03 Jun 2019 13:42:33 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-1905-13538.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Contributions
- Downloads last month
- 133