metadata

dataset_info:
  features:
    - name: image
      dtype:
        image:
          mode: RGB
    - name: label
      dtype:
        class_label:
          names:
            '0': Basophil
            '1': Eosinophil
            '2': Lymphocyte
            '3': Monocyte
            '4': Neutrophil
  splits:
    - name: cropped
      num_bytes: 67705296.008
      num_examples: 1407
    - name: augmented
      num_bytes: 38799344.112
      num_examples: 1464
    - name: original
      num_bytes: 1215365418
      num_examples: 285
  download_size: 1293100320
  dataset_size: 1321870058.12
configs:
  - config_name: default
    data_files:
      - split: cropped
        path: data/cropped-*
      - split: augmented
        path: data/augmented-*
      - split: original
        path: data/original-*
license: cc-by-4.0
task_categories:
  - image-classification
language:
  - en
tags:
  - veterinary
  - cell classification
  - animal
  - endangered species
  - microscopy
  - microscopic biological image
  - pig
  - blood cell
  - white blood cell
  - cell counting
pretty_name: >-
  Dataset for Machine Learning-Based Classification of White Blood Cells of the
  Juvenile Visayan Warty Pig
size_categories:
  - 1K<n<10K

WartyPig Dataset

Dataset Description

Homepage: WartyPig Dataset

Description

This dataset was prepared to aid in the creation of a machine learning algorithm that would classify the white blood cells in thin blood smears of juvenile Visayan warty pigs. The creation of this dataset was deemed imperative because of the limited availability of blood smear images collected from the critically endangered species on the internet. The dataset contains 3,457 images of various types of white blood cells (JPEG).

Citations

@data{3qsb-d447-22,
  title     = {Dataset for Machine Learning-Based Classification of White Blood Cells of the Juvenile Visayan Warty Pig},
  author    = {Alipo-on, Jacqueline Rose and Escobar, Francesca Isabelle and Novia, Jemima Loise and Atienza, Monica Marie and Mana-ay, Sonny and Tan, Myles Joshua and AlDahoul, Nouar and Yu, Evan},
  year      = 2022,
  publisher = {IEEE Dataport},
  doi       = {10.21227/3qsb-d447},
  url       = {https://dx.doi.org/10.21227/3qsb-d447}
}