| --- |
| 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 |
|
|
| ```bibtex |
| @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 |
|
|
