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dataset_info:
features:
- name: image
dtype: image
- name: objects
struct:
- name: bbox
list:
list: int64
- name: categories
list:
class_label:
names:
'0': whitefly
- name: abundance_level
dtype: string
splits:
- name: train
num_bytes: 3641888361
num_examples: 3000
download_size: 4121192636
dataset_size: 3641888361
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Cassava Whitefly Detection
This dataset contains real-world RGB images of cassava plants in field conditions from Namulonge, Uganda, focusing on detecting whitefly infestations. Images were captured using a handheld smartphone (Tecno Spark 3) under natural field environments, providing practical examples for agricultural computer vision applications. The dataset contains 3,000 images with 212,951 bounding box annotations across 1 category.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{nakatumbanabende2022dataset,
title={A dataset of cassava whitefly count images},
author={Nakatumba-Nabende, Joyce and Tusubira, Jeremy Francis and Babirye, Claire and Nsumba, Solomon and Abu, Christopher Omongo},
journal={Data in Brief},
volume={41},
pages={107911},
year={2022},
publisher={Elsevier}
}
```
Tusubira, Jeremy (2022), “Cassava Whitefly Dataset”, Mendeley Data, V3, doi: 10.17632/5g38399z9p.3
*This dataset was reformatted from its original format to match HuggingFace standards.*
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