Project-AgML/banana_guava_quality_classification

Banana Guava Quality Classification

A dataset for quality classification of bananas and guavas. The dataset contains 1,748 images across 3 classes: Class_A, Class_B, Defect.
Images per class:

• Class_A: 671
• Class_B: 469
• Defect: 608

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

Citation

@article{kumari2024banana,
  title={Banana and Guava dataset for machine learning and deep learning-based quality classification},
  author={Kumari, Abiban and Singh, Jaswinder},
  journal={Data in Brief},
  volume={57},
  pages={111025},
  year={2024},
  publisher={Elsevier}
}

KUMARI, ABIBAN; Singh, Jaswinder (2024), “Fruits (Banana and Guava) datasets for non-destructive quality classifications”, Mendeley Data, V2, doi: 10.17632/56td5w4wz2.2