Vegetable Recognition Dataset

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


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.



Meerut Institute of Engineering and Technology


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