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

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.

搜集汇总

背景与挑战

背景概述

VegNet是一个图像数据集，包含四种印度常见蔬菜（甜椒、番茄、辣椒和新墨西哥辣椒）的6850张图像，每张图像按质量状态分为未成熟、成熟、陈旧、干燥或损坏五类。该数据集旨在为蔬菜分类或识别机器学习模型提供训练、测试和验证支持，结构清晰，便于实际应用。