---
license: mit
pipeline_tag: image-to-text
datasets:
- antoniorv6/grandstaff
tags:
- omr
- camera_grandstaff
arxiv: 2402.07596
---

# Sheet Music Transformer (base model, fine-tuned on the Grandstaff dataset)

The SMT model fine-tuned on the _Camera_ GrandStaff dataset for pianoform transcription.
The code of the model is hosted in [this repository](https://github.com/antoniorv6/SMT).

## Model description

The SMT model consists of a vision encoder (ConvNext) and a text decoder (classic Transformer). 
Given an image of a music system, the encoder first encodes the image into a tensor of embeddings (of shape batch_size, seq_len, hidden_size), after which the decoder autoregressively generates text, conditioned on the encoding of the encoder. 

<img src="https://github.com/antoniorv6/SMT/raw/master/graphics/SMT.jpg" alt="drawing" width="720"/>

## Intended uses & limitations

This model is fine-tuned on the GrandStaff dataset, its use is limited to transcribe pianoform images only.

### BibTeX entry and citation info

```bibtex
@misc{RiosVila2024,
      title={Sheet Music Transformer: End-To-End Optical Music Recognition Beyond Monophonic Transcription}, 
      author={Antonio Ríos-Vila and Jorge Calvo-Zaragoza and Thierry Paquet},
      year={2024},
      eprint={2402.07596},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2402.07596}, 
}
```