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:
- n<1K
task_categories:
- image-to-text
- image-segmentation
- text-retrieval
subtasks:
- document-retrieval
extra_gated_fields:
Affiliation: text
dataset_info:
features:
- name: image
dtype: image
- name: id
dtype: string
- name: annotation
dtype: string
splits:
- name: train
num_bytes: 171465883
num_examples: 293
download_size: 137007918
dataset_size: 171465883
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Dataset
How to use
Check the following code:
import ast
from datasets import load_dataset
from PIL import ImageDraw
DATASET_NAME = "PRAIG/JAZZMUS"
ds = load_dataset(DATASET_NAME)
image = ds["train"][0]["image"]
# list of systems, with bounding boxes and encoding
systems = ast.literal_eval(ds["train"][0]["annotation"])["systems"]
# full page encodings
encoding = ast.literal_eval(ds["train"][0]["annotation"])["encodings"]
mxml_encoding = encoding["musicxml"]
kern_encoding = encoding["**kern"]
# draw the bounding boxes on the image
ImageDraw = ImageDraw.Draw(image)
for idx, s in enumerate(systems):
print(f"System {idx + 1}:")
print(f"\t{s['bounding_box']}")
print(f"\t{repr(s['**kern'])}\n")
bbox = s["bounding_box"]
ImageDraw.rectangle(
[bbox["fromX"], bbox["fromY"], bbox["toX"], bbox["toY"]],
outline="red",
width=2,
)
image.save("image_with_bboxes.pdf", "PDF")
Citation