Datasets:
File size: 3,584 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: latex
dtype: string
- name: latex_norm
dtype: string
- name: page_id
dtype: string
- name: expr_type
dtype: string
splits:
- name: train
num_bytes: 222324499.18
num_examples: 103940
- name: val
num_bytes: 41861369.289
num_examples: 18371
- name: test
num_bytes: 94309716.225
num_examples: 44383
download_size: 340062142
dataset_size: 358495584.694
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
task_categories:
- image-to-text
tags:
- latex
- math
- ocr
size_categories:
- 100K<n<1M
---
# IBEM Cropped: Bounding Box Mathematical Expressions from Scientific Pages
A processed version of the **IBEM Dataset** (Anitei et al., 2023), designed for the training and evaluation of image-to-markup models, expression recognition, and related document understanding tasks. Each sample in this dataset consists of a cropped image region containing a **single mathematical expression** (either displayed or embedded), along with its corresponding LaTeX annotations.
## Dataset Summary
This dataset is derived from the original **IBEM dataset** by extracting individual mathematical expressions using the provided bounding boxes, and cropping them from their original document pages. All page-level coordinates were specified as percentages and converted to absolute pixel coordinates during cropping.
Each record includes:
- A cropped image of the mathematical expression.
- The original LaTeX string (`latex`).
- A normalized LaTeX string (`latex_norm`) with visual formatting removed.
- The ID of the original page.
- The expression type (`isolated` or `embedded`).
## Dataset Structure
**Features:**
```python
features = Features({
"image": Image(),
"latex": Value("string"),
"latex_norm": Value("string"),
"page_id": Value("string"),
"expr_type": Value("string"),
})
````
**Splits:**
The dataset is split into standard `train`, `val`, and `test` subsets based on the official partition lists provided by the authors (`Tr*.lst`, `Va*.lst`, `Ts*.lst`).
## Source
**Citation:**
> Anitei, D., Sánchez, J. A., & Benedí, J. M. (2023). The IBEM Dataset: a large printed scientific image dataset for indexing and searching mathematical expressions (1.0) \[Data set]. Zenodo. [https://doi.org/10.5281/zenodo.7963703](https://doi.org/10.5281/zenodo.7963703)
## Original Dataset Description
The IBEM dataset consists of 600 LaTeX documents with a total of 8,272 pages, containing:
* **29,603 displayed mathematical expressions**
* **137,089 embedded mathematical expressions**
These were extracted from the LaTeX source files of documents in the **KDD Cup Collection**. The dataset supports a variety of tasks, including:
* Mathematical expression detection and extraction
* LaTeX recognition from printed page images
* Indexing and search of STEM content in large-scale document archives
## Preprocessing Notes
* **Preamble fields** containing LaTeX macros were excluded.
* All expressions were **cropped** to their respective bounding boxes and stored as image snippets.
* Only the `latex` and `latex_norm` fields were retained for expression text.
* Expressions split across multiple lines were treated as-is, using the duplicated complete LaTeX string provided by the original dataset.
## Licensing
Distributed under the same license as the original IBEM dataset.
Creative Commons Attribution 4.0 International |