| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: latex |
| dtype: string |
| - name: sample_id |
| dtype: string |
| - name: split_tag |
| dtype: string |
| - name: data_type |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1308313988.28 |
| num_examples: 229864 |
| - name: test |
| num_bytes: 50449700.38 |
| num_examples: 7644 |
| - name: val |
| num_bytes: 92725986.108 |
| num_examples: 15674 |
| download_size: 1247446895 |
| dataset_size: 1451489674.7680001 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| - split: val |
| path: data/val-* |
| task_categories: |
| - image-to-text |
| tags: |
| - math |
| - latex |
| - handwritten |
| - ocr |
| size_categories: |
| - 100K<n<1M |
| --- |
| # Dataset Card for MathWriting |
|
|
| ## Dataset Summary |
|
|
| The **MathWriting** dataset contains online handwritten mathematical expressions collected through a prompted interface and rendered to RGB images. It consists of **230,000 human-written expressions**, each paired with its corresponding LaTeX string. The dataset is intended to support research in **online and offline handwritten mathematical expression (HME) recognition**. |
|
|
| Key features: |
|
|
| - Online handwriting converted to rendered RGB images. |
| - Each sample is labeled with a LaTeX expression. |
| - Includes splits: `train`, `val`, and `test`. |
| - All samples in this release are **human-written** (no synthetic data). |
| - Image preprocessing includes resizing (max dimension ≤ 512 px), stroke width jitter, and subtle color perturbations. |
|
|
| --- |
|
|
| ## Supported Tasks and Leaderboards |
|
|
| **Primary Task:** |
| - *Handwritten Mathematical Expression Recognition (HMER)*: Given an image of a handwritten formula, predict its LaTeX representation. |
|
|
| This dataset is also suitable for: |
| - Offline HME recognition (from rendered images). |
| - Sequence modeling and encoder-decoder learning. |
| - Symbol layout analysis and parsing in math. |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| Each example has the following structure: |
|
|
| ```python |
| { |
| 'image': <PIL.Image.Image in RGB mode>, |
| 'latex': str, # the latex string" |
| 'sample_id': str, # unique identifier |
| 'split_tag': str, # "train", "val", or "test" |
| 'data_type': str, # always "human" in this version |
| } |
| ``` |
|
|
| All samples are rendered from digital ink into JPEG images with randomized stroke width and light RGB variations for augmentation and realism. |
|
|
| ## Usage |
|
|
| To load the dataset: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("deepcopy/MathWriting-Human") |
| sample = ds["train"][0] |
| image = sample["image"] |
| latex = sample["latex"] |
| ``` |
|
|
| ## Licensing Information |
|
|
| The dataset is licensed by **Google LLC** under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International** license ([CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)). |
|
|
| --- |
|
|
| ## Citation |
|
|
| Please cite the following paper if you use this dataset: |
|
|
| ``` |
| @misc{gervais2025mathwritingdatasethandwrittenmathematical, |
| title={MathWriting: A Dataset For Handwritten Mathematical Expression Recognition}, |
| author={Philippe Gervais and Anastasiia Fadeeva and Andrii Maksai}, |
| eprint={2404.10690}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2404.10690}, |
| } |
| ``` |
