⚠️ 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:

1. Gain access to the dataset and get your HF access token from: https://huggingface.co/settings/tokens.
2. 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.
3. 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}
}