---
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.*