README.md

---
license: cc-by-nc-4.0
task_categories:
- image-classification
- image-to-text
viewer: false
---
# Math-Strike Dataset
## Dataset Description
**Math-Strike** is a novel dataset featuring real and synthetic strike-outs, component-level annotations, and aligned LaTeX, designed to support research on strike-out removal and handwritten mathematical formula recognition. Handwritten STEM manuscripts often contain strike-outs, overwrites, and other markings that disrupt mathematical content structure and reduce OCR/VLM recognition accuracy. This dataset provides a rigorous benchmark for training and evaluating models on connected-component classification, geometry-aware inpainting, and downstream compilable LaTeX generation.

The collection originates from the 2024-2025 mid-term and final examinations of a university's Multivariate Calculus Elite class. 

### Dataset Subsets
The dataset is divided into two main subsets, easily accessible via Hugging Face's configuration system:
- **`real` (Math-Strike-Real)**: Contains only real, authentic strike-outs collected directly from student exam papers.
- **`synth` (Math-Strike-Synth)**: Contains synthetic strike-outs generated using an augmentation taxonomy of 20 diverse strike-out styles (e.g., wavy, zigzag, multi-crossed, blackout) to address class imbalance and improve model robustness against complex occlusion patterns.
Additionally, the `original_img` folder is provided in the repository, containing the full page-level raw scans with minimal border cropping and all original marks.

## Dataset Structure
### Data Instances
When loading the dataset via the `datasets` library, each instance represents a single connected component extracted from the manuscript.
### Data Fields
| Field | Type | Description |
| :--- | :--- | :--- |
| `id` | int | Global component identifier. |
| `page_img` | string | Source page filename. |
| `bbox` | list | Bounding box coordinates in pixels. |
| `centroid` | list | Geometric centre (x, y) of the component. |
| `box_area` / `pixel_area` | int | Foreground-pixel count within the component. |
| `label` | int | 0 = retained (valid mathematical symbol), 1 = removed (strike-out/noise). |
| `comp_size` | list | Height and width of the bounding box. |
| `image` | Image | The actual cropped PNG image of the component. |
| `file` | string | The actual path of the image. |

## Usage
You can easily load the dataset using the Hugging Face `datasets` library. The images and metadata are already pre-aligned in Parquet format.
```python
from datasets import load_dataset

# Load the subset with real strike-outs
dataset_real = load_dataset("Incinciblecolonel/MathStrike", name="real")

# Load the subset with synthetic strike-outs
dataset_synth = load_dataset("Incinciblecolonel/MathStrike", name="synth")

# Access the training split
train_data = dataset_real["train"]
print(train_data[0]) 

# Directly visualize the component image
train_data[0]["image"].show()
```

## Alternative Download (Raw Files)
For researchers who prefer downloading the raw image folders and JSON annotations directly instead of using the `datasets` library, the complete archived dataset (ZIP) is hosted on Kaggle:

👉 **[Download Math-Strike on Kaggle](https://www.kaggle.com/datasets/senshen1020/mathscrub-handwritten-calculus-strike-out-dataset)**


## License
The Math-Strike dataset is distributed under the **CC-BY-NC 4.0** license for non-commercial research and educational use.

## Citation
If you find this dataset useful for your research, please cite our paper:

```
@article{shen2026mathscrub,
  title={MathScrub: Single-Pipeline Strike-Out Removal and LaTeX Generation for Handwritten Calculus Expressions},
  author={Shen, Sen and Liu, Ning and Song, Lintao and Han, Dongkun},
  journal={IEEE Transactions on Learning Technologies},
  year={2026},
  publisher={IEEE}
}
```