README.md

---
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- n<1K
language:
- en
tags:
- cotton-ball
- cotton
- object-detection
---

# CBDA — Cotton Ball Detection Dataset for Agriculture (Augmented)

A UAV-imagery dataset for cotton ball detection and counting on cotton crops. The dataset contains 180 images with 5,333 annotated cotton ball instances (single class: `cotton_ball`). Bounding boxes are in COCO format `[x, y, width, height]`.

This augmented version extends the original CBDA collection with additional synthetic samples to improve model robustness across varying altitudes, lighting conditions, and crop densities.

| Split | Images | Annotations |
|-------|--------|-------------|
| train | 180 | 5,333 |

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Loading

```python
from datasets import load_dataset

ds = load_dataset("Project-AgML/CBDA_Cotton_Ball_Detection_Augmented")
```

# Citation

```bibtex
@article{amrani2023plant,
  title={Plant Detection and Counting: Enhancing Precision Agriculture in UAV and General Scenes},
  author={Amrani, Moussa and Sohel, Ferdous and Murray, Neil and Hazel, Susan},
  journal={IEEE Access},
  year={2023},
  publisher={IEEE}
}

Amrani, Moussa; Sohel, Ferdous; Murray, Neil; Hazel, Susan (2023), "Plant Detection and Counting: Enhancing Precision Agriculture in UAV and General Scenes", IEEE Access
```