metadata
configs:
- config_name: default
default: true
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Bean
'1': Bitter melon
'2': Brinjal
'3': Cucumber
'4': Garlic
'5': Green Chili
'6': Ladies finger
'7': Onion
'8': Pointed gourd
'9': Potato
'10': Radish
'11': Tomato
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
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