VegNet: Vegetable Dataset with quality (Good & Bad quality)

Published: 11 July 2022| Version 3 | DOI: 10.17632/73n5hrn8hh.3
Prawit Chumchu


Neat and clean dataset is the elementary requirement to build accurate and robust machine learning models for the real-time environment. With this objective we have created an image dataset of Indian four vegetable with quality parameter which are highly consumed or exported. Accordingly, we have considered four vegetables namely Bell Pepper, Tomato, Chili Pepper, and New Mexico Chile to create a dataset. The dataset is categorized into 4 subfolders of vegetables namely bell pepper, tomato, Chili Pepper, and New Mexico Chile. Further each vegetable folder contains four subfolders namely 1) Multiple Mature, 2) Single Mature, 3) Multiple Over Mature, and 4) Single Over Mature vegetable classes. Total 6793 images are available in the dataset. We strongly believe that the proposed dataset is very helpful for training, testing and validation of vegetable classification or reorganization machine leaning model.



Machine Learning