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Project-AgML/vegetable_classification_bangladesh

Vegetable Classification Banglades A dataset for image classification of various types of vegetables. The dataset contains 4,319 images across 12 classes: Bean, Bitter melon, Brinjal, Cucumber, Garlic, Green Chili, Ladies finger, Onion, Pointed gourd, Potato, Radish, Tomato. Images per class: Bean: 454 Bitter melon: 306 Brinjal: 373 Cucumber: 342 Garlic: 349 Green Chili: 497 Ladies finger: 308 Onion: 357 Pointed gourd: 329 Potato: 365 Radish: 310 Tomato: 329 This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/vegetable_classification_bangladesh.

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Dataset Card

Vegetable Classification Banglades

A dataset for image classification of various types of vegetables. The dataset contains 4,319 images across 12 classes: Bean, Bitter melon, Brinjal, Cucumber, Garlic, Green Chili, Ladies finger, Onion, Pointed gourd, Potato, Radish, Tomato. Images per class:

—Bean: 454
—Bitter melon: 306
—Brinjal: 373
—Cucumber: 342
—Garlic: 349
—Green Chili: 497
—Ladies finger: 308
—Onion: 357
—Pointed gourd: 329
—Potato: 365
—Radish: 310
—Tomato: 329

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

Citation

bibtex

@article{ahmed2025banglaveg,
  title={BanglaVeg: A curated vegetable image dataset from Bangladesh for precision agriculture},
  author={Ahmed, Md Jobayer and Saha, Ratu and Dutta, Arpon Kishore and Mojumdar, Mayen Uddin and Chakraborty, Narayan Ranjan},
  journal={Data in Brief},
  volume={59},
  pages={111441},
  year={2025},
  publisher={Elsevier}
}

Ahmed, Md Jobayer; Saha, Ratu; Dutta , Arpon Kishore ; Mojumdar, Mayen Uddin (2025), “Vegetable Image Dataset for Classification Models: A Bangladeshi Perspective”, Mendeley Data, V4, doi: 10.17632/b9rvg4f2st.4