Vegetable Image Dataset for Classification Models: A Bangladeshi Perspective

Published: 18 November 2024| Version 1 | DOI: 10.17632/b9rvg4f2st.1
Contributors:
Md Jobayer Ahmed,
,
, Mayen Uddin Mojumdar

Description

Dataset overview: This dataset includes a total of 2,947 labeled images representing various vegetables commonly found in Bangladesh, designed for machine learning, computer vision research, and agricultural studies. Dataset Breakdown by Vegetable Type: Potato: 272 images Onion: 357 images Green Chili: 497 images Garlic: 235 images Radish: 310 images Bean: 454 images Ladies Finger : 213 images Cucumber: 232 images Pointed Gourd: 157 images Bitter Melon: 93 images Brinjal (Eggplant): 88 images Tomato: 37 images Data Source: The images were captured using mobile phone cameras, and the backgrounds were removed to enhance the clarity and focus on the vegetables. Applications: Vegetable Classification Models Automated Produce Recognition Systems Computer Vision Benchmarking Educational and Agricultural Research

Files

Institutions

Daffodil International University

Categories

Vegetable, Image Classification

Licence