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

Citation

@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