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End of preview. Expand in Data Studio
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
YOLO Dataset — Flat & Alto Clef Detection
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']
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