Datasets:

Project-AgML
/

CBDA_Cotton_Ball_Detection_Augmented

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

from datasets import load_dataset

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

Citation

@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