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--- |
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license: cc-by-4.0 |
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task_categories: |
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- object-detection |
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tags: |
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- roboflow |
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- roboflow-100 |
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- rf100 |
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- yolo |
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- libreyolo |
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- real-world |
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- computer-vision |
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- bounding-box |
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pretty_name: "Peanuts Sd4Kf" |
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size_categories: |
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- 1K<n<10K |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: string |
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splits: |
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- name: train |
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num_examples: 268 |
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- name: validation |
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num_examples: 77 |
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- name: test |
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num_examples: 42 |
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--- |
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# Peanuts Sd4Kf |
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This dataset is part of the **Roboflow 100** benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains. |
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## Dataset Description |
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- **Source:** [Roboflow 100](https://github.com/roboflow/roboflow-100-benchmark) |
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- **Category:** Real World |
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- **License:** CC-BY-4.0 |
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- **Format:** YOLO (LibreYOLO compatible) |
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- **Mirrored on:** 2026-01-20 |
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## Dataset Statistics |
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| Split | Images | |
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|-------|--------| |
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| Train | 268 | |
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| Validation | 77 | |
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| Test | 42 | |
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| **Total** | **387** | |
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## Classes (2) |
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- with mold |
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- without mold |
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## Usage |
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### With LibreYOLO |
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```python |
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from libreyolo import LIBREYOLO |
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# Load a model |
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model = LIBREYOLO(model_path="libreyoloXnano.pt") |
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# Train on this dataset |
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model.train(data='path/to/data.yaml', epochs=100) |
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``` |
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### Download from HuggingFace |
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```python |
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from huggingface_hub import snapshot_download |
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# Download the dataset |
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snapshot_download( |
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repo_id="Libre-YOLO/peanuts-sd4kf", |
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repo_type="dataset", |
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local_dir="./peanuts-sd4kf" |
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) |
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``` |
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## Directory Structure |
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``` |
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peanuts-sd4kf/ |
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├── data.yaml # Dataset configuration |
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├── README.md # This file |
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├── train/ |
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│ ├── images/ # Training images |
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│ └── labels/ # Training labels (YOLO format) |
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├── valid/ |
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│ ├── images/ # Validation images |
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│ └── labels/ # Validation labels |
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└── test/ |
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├── images/ # Test images (if available) |
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└── labels/ # Test labels |
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``` |
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## Label Format |
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Labels are in YOLO format (one `.txt` file per image): |
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``` |
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<class_id> <x_center> <y_center> <width> <height> |
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``` |
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All coordinates are normalized to [0, 1]. |
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## Citation |
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If you use this dataset, please cite the Roboflow 100 benchmark: |
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```bibtex |
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@misc{rf100_2022, |
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Author = {Floriana Ciaglia and Francesco Saverio Zuppichini and Paul Guerrie and Mark McQuade and Jacob Solawetz}, |
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Title = {Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark}, |
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Year = {2022}, |
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Eprint = {arXiv:2211.13523}, |
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} |
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``` |
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## License |
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This dataset is released under the **CC-BY-4.0** license. |
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Please check the original source for any additional terms. |
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## Acknowledgments |
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- Original dataset from [Roboflow Universe](https://universe.roboflow.com/roboflow-100/peanuts-sd4kf) |
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- Part of the [Roboflow 100 Benchmark](https://www.rf100.org/) |
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- Sponsored by Intel |
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