README.md

metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: maturity
      dtype: string
    - name: variety
      dtype: string
    - name: objects
      struct:
        - name: bbox
          list:
            list: float64
        - name: categories
          list:
            class_label:
              names:
                '0': Cacao
  splits:
    - name: train
      num_bytes: 5623755048
      num_examples: 1254
  download_size: 5879636996
  dataset_size: 5623755048
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - object-detection
size_categories:
  - 1K<n<10K

CocoaMFDB Detection Object Detection

A dataset for detection of cocoa pods. The dataset contains 1,254 images with 1,482 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{ayikpa2023cocoamfdb,
  title={CocoaMFDB: A dataset of cocoa pod maturity and families in an uncontrolled environment in C{\^o}te d'Ivoire},
  author={Ayikpa, Kacoutchy Jean and Mamadou, Diarra and Ballo, Abou Bakary and Yao, Konan and Gouton, Pierre and Adou, Kablan J{\'e}r{\^o}me},
  journal={Data in Brief},
  volume={48},
  pages={109196},
  year={2023},
  publisher={Elsevier}
}

AYIKPA, Kacoutchy Jean (2022), “CocoaMFDB”, Mendeley Data, V2, doi: 10.17632/9msjjh3np6.2

This dataset was reformatted from its original format to match HuggingFace standards.