marbles / README.md
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---
license: cc-by-4.0
task_categories:
- object-detection
tags:
- roboflow
- roboflow-100
- rf100
- yolo
- libreyolo
- real-world
- computer-vision
- bounding-box
pretty_name: "Marbles"
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: string
splits:
- name: train
num_examples: 54
- name: validation
num_examples: 19
- name: test
num_examples: 32
---
# Marbles
This dataset is part of the **Roboflow 100** benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains.
## Dataset Description
- **Source:** [Roboflow 100](https://github.com/roboflow/roboflow-100-benchmark)
- **Category:** Real World
- **License:** CC-BY-4.0
- **Format:** YOLO (LibreYOLO compatible)
- **Mirrored on:** 2026-01-20
## Dataset Statistics
| Split | Images |
|-------|--------|
| Train | 54 |
| Validation | 19 |
| Test | 32 |
| **Total** | **105** |
## Classes (2)
- red
- white
## Usage
### With LibreYOLO
```python
from libreyolo import LIBREYOLO
# Load a model
model = LIBREYOLO(model_path="libreyoloXnano.pt")
# Train on this dataset
model.train(data='path/to/data.yaml', epochs=100)
```
### Download from HuggingFace
```python
from huggingface_hub import snapshot_download
# Download the dataset
snapshot_download(
repo_id="Libre-YOLO/marbles",
repo_type="dataset",
local_dir="./marbles"
)
```
## Directory Structure
```
marbles/
├── data.yaml # Dataset configuration
├── README.md # This file
├── train/
│ ├── images/ # Training images
│ └── labels/ # Training labels (YOLO format)
├── valid/
│ ├── images/ # Validation images
│ └── labels/ # Validation labels
└── test/
├── images/ # Test images (if available)
└── labels/ # Test labels
```
## Label Format
Labels are in YOLO format (one `.txt` file per image):
```
<class_id> <x_center> <y_center> <width> <height>
```
All coordinates are normalized to [0, 1].
## Citation
If you use this dataset, please cite the Roboflow 100 benchmark:
```bibtex
@misc{rf100_2022,
Author = {Floriana Ciaglia and Francesco Saverio Zuppichini and Paul Guerrie and Mark McQuade and Jacob Solawetz},
Title = {Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark},
Year = {2022},
Eprint = {arXiv:2211.13523},
}
```
## License
This dataset is released under the **CC-BY-4.0** license.
Please check the original source for any additional terms.
## Acknowledgments
- Original dataset from [Roboflow Universe](https://universe.roboflow.com/roboflow-100/marbles)
- Part of the [Roboflow 100 Benchmark](https://www.rf100.org/)
- Sponsored by Intel