Vegetable Recognition Dataset

Published: 16 April 2024| Version 1 | DOI: 10.17632/chv7dmvtfm.1
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Description

An extensive dataset featuring over 8000 high-resolution images, with a diverse selection of 8 commonly utilized Indian vegetables: potato, tomato, ginger, garlic, chili, brinjal, carrot, and onion. This comprehensive collection encompasses a breadth of environmental conditions, including plain, cluttered, and natural backgrounds, as well as varied lighting scenarios such as bright and low-light conditions . The images offer a range of perspectives, from close-up shots to faraway angles, capturing the vegetables in different conditions. Every image within the dataset is meticulously self-clicked, ensuring authenticity and diversity in location, including markets, fields, and households. Explore this rich resource for robust insights and applications in image recognition, agriculture, and beyond.

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Institutions

Meerut Institute of Engineering and Technology

Categories

Machine Learning, Vegetable, Image Classification, Convolutional Neural Network, Deep Learning, Deep Neural Network

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