Models

The model comes with a set of arguments that were used to create it. The latest model is trained on the latest dataset.

Datasets

Datasets

The final dataset is split into four logical parts:

• AudioLabs v2
• Muscima++
• OSLiC
• MZKBlank

Due to GitHub's restrictions on file size, the OSLiC dataset is split into two parts. OSLiC in COCO format keeps the same folder structure as the original dataset.

Quick Start

To train a YOLO model on the datasets, download all archives that are not tagged with COCO and combine them into one. When setting up the training pass the config.yaml file as an argument to to the script.

Dataset Overview

	images	system measures	stave measures	staves	systems	grand staves
AudioLabs v2	940	24 186	50 064	11 143	5 376	5 375
Muscima++	140	2 888	4 616	883	484	94
OSLiC	4 927	72 028	220 868	55 038	17 991	17 959
MZKBlank	1 006	0	0	0	0	0
total	7 013	99 102	275 548	67 064	23851	23 428

COCO format

zip/
    img/     ... all images
    json/  ... corresponding labels in COCO format

{
 "width": 3483,
 "height": 1693,
 "system_measures": [
  {
   "left": 211,
   "top": 726,
   "width": 701,
   "height": 120
  },
...

YOLO format

zip/
    images/    ... all images
    labels/      ... corresponding labels in YOLO format

The *.txt file is formatted with one row per object in class x_center y_center width height format. Box coordinates must be in normalized xywh format (from 0 to 1).

0	0.163365	0.429003	0.205570	0.090634
0	0.328309	0.429003	0.112834	0.090634
0	0.462245	0.429003	0.138961	0.090634
0	0.598048	0.429003	0.124605	0.090634
0	0.741746	0.429003	0.150158	0.090634
0	0.889176	0.429003	0.136090	0.090634