| --- |
| 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 |
|
|
| ```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 |
