Datasets:
Search is not available for this dataset
image imagewidth (px) 1.18k 8k | label class label 3
classes |
|---|---|
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade | |
23rd-grade |
End of preview. Expand in Data Studio
AFruitDB Fruit Grade Classification
A dataset for grade classification of 6 fruits: tomato, papaya, mango, Burmese grape, apple, and banana. The dataset contains 3,167 images across 3 classes: 1st-grade, 2nd-grade, 3rd-grade. Images per class:
- 1st-grade: 1,297
- 2nd-grade: 1,196
- 3rd-grade: 674
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{mojumdar2025afruitdb,
title={AFruitDB: A comprehensive dataset of six commonly used Asian fruits for advanced grading and biodiversity insights},
author={Mojumdar, Mayen Uddin and Islam, Shahrin and Al Mamun, Md and Hasan, Rifat and Siddiquee, Shah Md Tanvir and Chakraborty, Narayan Ranjan},
journal={Data in Brief},
volume={59},
pages={111380},
year={2025},
publisher={Elsevier}
}
Mojumdar, Mayen Uddin ; Mamun, Md Al ; Islam, Shahrin; Hasan, Rifat (2024), “A Dataset of Common Asian Fruits for Quality Grading and Biodiversity Research”, Mendeley Data, V1, doi: 10.17632/bz65dz2pbj.1
- Downloads last month
- 19