metadata

license: cc-by-nc-4.0
tags:
  - music
  - documents
  - end-to-end
  - full-page
  - system-level
annotations_creators:
  - manually expert-generated
pretty_name: Jazzmus
size_categories:
  - 1K<n<10K
task_categories:
  - image-to-text
  - image-segmentation
  - text-retrieval
subtasks:
  - document-retrieval
extra_gated_fields:
  Affiliation: text

⚠️ Work in Progress! JAZZMUS ⚠️

Overview

JAZZMUS is a dataset of handwritten jazz lead sheet scores developed at the University of Alicante at the Pattern Recognition and Artificial Intelligence Group.

Use Cases:

Optical Music Recognition (OMR): system-level, full-page
Image Segmentation: music regions

Dataset Details

Each page includes the corresponding agnostic symbol sequences.

JAZZMUS usage 📖

JAZZMUS is available upon request at HuggingFace.

To download from HuggingFace:

Gain access to the dataset and get your HF access token from: https://huggingface.co/settings/tokens.
Install dependencies and login HF:
- Install Python
- Run pip install pillow datasets huggingface_hub[cli]
- Login by huggingface-cli login and paste the HF access token. Check here for details.
Use the following code to load SMB and extract the regions:

import datasets
import matplotlib.pyplot as plt

# Here we just load 10 samples
jazzmus_d = datasets.load_dataset("PRAIG/JAZZMUS", split="train[:10]")

ID = 6 # score id
music = jazzmus_d[ID]["regions"]["music"]
chords = jazzmus_d[ID]["regions"]["chords"]
both = jazzmus_d[ID]["regions"]["both"]

plt.figure(figsize=(10, 10))

def plot_box(bbox, color, alpha=0.5):
    box = bbox["bounding_box"]
    fromx, fromy, tox, toy = box["fromX"], box["fromY"], box["toX"], box["toY"]
    x, y = fromx, fromy
    w, h = tox - fromx, toy - fromy

    plt.gca().add_patch(
        plt.Rectangle((x, y), w, h, fill=False, edgecolor=color, lw=1.5, alpha=alpha)
    )


for bbox_m, bbox_c, bbox_b in zip(music, chords, both):
    plot_box(bbox_m, "red")
    plot_box(bbox_c, "blue")
    plot_box(bbox_b, "green")


plt.tight_layout()
plt.axis("off")

plt.imshow(jazzmus_d[ID]["image"])

Citation

If you use our work, please cite us:

@preprint{,
  author = {},
  title = {},
  year = {2025}
}