Image dataset of pomegranate fruits (Punica granatum) for various machine vision applications
Arun Kumar R, Vijay S. Rajpurohit, Nilesh Gaikwad
Abstract
Dataset - an essential aspect and the requirement for any of the machine learning project. Collection/creation of dataset in the agriculture domain is highly challenging task because the domain itself is uncertain. Main objective of the present paper is to create an image dataset of pomegranate fruits of different grades. Accordingly, we have considered 'Ruby' cultivar of pomegranate and sincerely constructed the dataset. Fruits belonging to three grades are considered. The images for each fruit are covered from all the three angles. The dataset created also contains the weights of the fruits. The dataset consists of 12 folders named after their effective quality grades. The usage of this dataset is already proved in the works carried out by the authors in their previous studies. This dataset is highly helpful for the data science engineer / machine learning programmer or machine learning expert working in the field of precision agriculture.