Datasets:

Project-AgML
/

cotton_weed_detection

configs:
  - config_name: default
    default: true
    features:
      - name: image
        dtype: image
      - name: objects
        sequence:
          - name: bbox
            list: float32
          - name: categories
            class_label:
              names:
                '0': weed
                '1': cotton
license: cc-by-4.0
task_categories:
  - object-detection
size_categories:
  - n<1K

Cotton Weed Detection

A dataset for weed detection in cotton fields. The dataset contains 262 images with 50,812 bounding box annotations across 2 categories, weed and cotton.

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

Citation

@article{das2026uav,
  title={A UAV Image Dataset for Object Detection with Annotations Generated Using LabelImg and Roboflow},
  author={Das, Anindita and Subburaj, Vinitha Hannah and Yang, Yong and Bednarz, Craig W},
  journal={Data in Brief},
  pages={112483},
  year={2026},
  publisher={Elsevier}
}

Das, Anindita; Subburaj, Vinitha; Yang, Yong; Bednarz, Craig (2025), “A UAV Image Dataset for Object Detection with Annotations Generated Using LabelImg and Roboflow ”, Mendeley Data, V1, doi: 10.17632/sx2tphzvcw.1