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---
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

```bibtex
@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.*