Vegetable Image Dataset for Classification Models: A Bangladeshi Perspective

Published: 19 February 2025| Version 4 | DOI: 10.17632/b9rvg4f2st.4
Contributors:
Md Jobayer Ahmed,
,
, Mayen Uddin Mojumdar

Description

Dataset overview: This dataset includes a total of 4319 raw images representing various vegetables commonly found in Bangladesh, designed for machine learning, computer vision research, and agricultural studies. Dataset Breakdown by Vegetable Type: Potato: 365 images Onion: 357 images Green Chili: 497 images Garlic: 349 images Radish: 310 images Bean: 454 images Ladies Finger : 308 images Cucumber: 342 images Pointed Gourd: 329 images Bitter Melon: 306 images Brinjal : 373 images Tomato: 329 images Data Source: The images were captured using mobile phone cameras and kept in their original form without any modifications, ensuring the preservation of natural backgrounds for better machine learning adaptability. 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