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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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/MangoClassify-12_variety_classification.

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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

bibtex

@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