FruitNet: Indian Fruits Dataset with quality (Good, Bad & Mixed quality)

Published: 8 March 2022| Version 3 | DOI: 10.17632/b6fftwbr2v.3


High quality images of fruits are required to solve fruit classification and recognition problem. To build the machine learning models, neat and clean dataset is the elementary requirement. With this objective we have created the dataset of six popular Indian fruits named as “FruitNet”. This dataset consists of 14700+ high-quality images of 6 different classes of fruits in the processed format. The images are divided into 3 sub-folders 1) Good quality fruits 2) Bad quality fruits and 3) Mixed quality fruits. Each sub-folder contains the 6 fruits images i.e. apple, banana, guava, lime, orange, and pomegranate. Mobile phone with a high-end resolution camera was used to capture the images. The images were taken at the different backgrounds and in different lighting conditions. The proposed dataset can be used for training, testing and validation of fruit classification or reorganization model. [The related article is available at: Cite the article as : V. Meshram, K. Patil, FruitNet: Indian fruits image dataset with quality for machine learning applications, Data in Brief, Volume 40, 2022, 107686, ISSN 2352-3409, ]



Artificial Intelligence, Computer Vision, Object Detection, Machine Learning, Fruit, Deep Learning