VegNet: Vegetable Dataset with quality (Unripe, Ripe, Old, Dried and Damaged)

Published: 21 September 2022| Version 1 | DOI: 10.17632/6nxnjbn9w6.1
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Description

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 five subfolders namely Unripe, Ripe, Old, Dried and Damaged. Total 6850 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 learning model.

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Horticulture, Machine Learning, Agriculture Industry, Vegetable Crops

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