Samruddhik268/cable-damage

---
license: cc-by-4.0
task_categories:
- object-detection
tags:
- roboflow
- roboflow-100
- rf100
- yolo
- libreyolo
- real-world
- computer-vision
- bounding-box
pretty_name: "Cable Damage"
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: string
splits:
- name: train
num_examples: 919
- name: validation
num_examples: 265
- name: test
num_examples: 134
---

# Cable Damage

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 | 919 |
| Validation | 265 |
| Test | 134 |
| **Total** | **1,318** |

## Classes (2)

- break
- thunderbolt

## 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/cable-damage",
repo_type="dataset",
local_dir="./cable-damage"
)
```

## Directory Structure

```
cable-damage/
├── 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/cable-damage)
- Part of the [Roboflow 100 Benchmark](https://www.rf100.org/)
- Sponsored by Intel