Datasets:

Project-AgML
/

Cassava_whitefly_detection

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

@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.