Project-AgML/MangoClassify-12_variety_classification

MangoClassify 12 Variety Classification

A dataset for variety classification of common mangoes. The dataset contains 3,900 images across 12 classes:
Images per class:

• Amrapali: 600
• Banana: 212
• Bari 4: 240
• Fazli: 120
• GobindoBhog: 41
• GopalBhog: 406
• Harivanga: 575
• Himsagar: 502
• Khrishapat: 380
• Langra: 506
• RaniBhog: 92
• Sundari: 226

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

Citation

@article{rahman2025mangoclassify,
  title={MangoClassify-12: A high-resolution image dataset of twelve indigenous Bangladeshi mango cultivars},
  author={Rahman, Md Sajedur and Nahin, Md Mahfuz Ahmed and Rahman, Md Mahbubur and Rani, Mollika and Islam, Md Ashraful and Bashir, Al and Shafkat, Ahmad and Mallik, Bijon and Majeed, Yaqoob},
  journal={Data in Brief},
  pages={112037},
  year={2025},
  publisher={Elsevier}
}

Md. Sajedur Rahman, Md. Mahfuz Ahmed Nahin, Mollika Rani, and MD Ashraful Islam. (2025). MangoClassify-12: Native Mango Dataset from BD [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/12460544