Datasets:

BowenC
/

flat_alto

A YOLO-format object detection dataset for recognising two music notation symbols on orchestral score images: flat accidentals and alto clefs.

Classes

ID	Name	Description
`0`	`flat`	Flat accidental (♭) appearing in key signatures or as an accidental before a note
`1`	`alto_clef`	Alto (C) clef, typically used for the viola staff

Dataset Statistics

Split	Images	`flat`	`alto_clef`
train	86	5390	411
val	20	1322	105
test	17	697	78
total	123	7409	594

Source Scores

Images are cropped staff lines drawn from 7 orchestral scores:

Score	Composer
beethoven7, beethoven8, beethoven10, beethoven11	Ludwig van Beethoven
mendelssohn1	Felix Mendelssohn
tchaikovsky0, tchaikovsky2	Pyotr Ilyich Tchaikovsky

Structure

dataset_yolo_flat_alto/
├── dataset.yaml            # YOLO dataset config
├── images/
│   ├── train/              # 86 images
│   ├── val/                # 20 images
│   └── test/               # 17 images
└── labels/
    ├── train/              # YOLO .txt annotations
    ├── val/
    └── test/

Image Naming

{score_name}_{staff_index}.jpg

Each image is a single cropped staff line extracted from the source score. For example, beethoven10_3.jpg is the 3rd staff crop from the score beethoven10.

Label Format

Labels follow the standard YOLO format — one .txt file per image, one bounding box per line:

<class_id> <x_center> <y_center> <width> <height>

All values are normalised to [0, 1] relative to the image dimensions.

Example:

0 0.417922 0.213076 0.006325 0.011066
1 0.081175 0.877258 0.017169 0.018744

YOLO Config

dataset.yaml:

train: images/train
val:   images/val
test:  images/test
nc: 2
names: ['flat', 'alto_clef']