Datasets:

Project-AgML
/

sapota_fruit_size_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Large
            '1': Medium
            '2': Small
            '3': Spoiled
  splits:
    - name: train
      num_bytes: 16876341
      num_examples: 6010
  download_size: 15845938
  dataset_size: 16876341
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

Sapota Fruit Size Classification

A dataset for classification of Sapota Fruit Size. The dataset contains 6,010 images across 4 classes: Large, Medium, Small, Spoiled.
Images per class:

Large: 1,451
Medium: 1,416
Small: 1,443
Spoiled: 1,700

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{bhatt2025dedicated,
  title={Dedicated dataset of Sapota (Manilkara zapota) fruit for machine vision applications},
  author={Bhatt, Anita and Joshi, Maulin},
  journal={Data in Brief},
  pages={111896},
  year={2025},
  publisher={Elsevier}
}

Bhatt, Anita; Joshi, Maulin (2025), “Sapota Fruit Datasets”, Mendeley Data, V2, doi: 10.17632/jgtb95x6kf.2

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