Vegetable Image Dataset for Classification Models: A Bangladeshi Perspective
收藏doi.org2025-03-26 收录
下载链接:
http://doi.org/10.17632/b9rvg4f2st.1
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资源简介:
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
数据集概述:本数据集总计包含2,947张标注图像,展现了孟加拉国常见各类蔬菜,旨在服务于机器学习、计算机视觉研究及农业研究之用。
数据集蔬菜类型分布如下:
土豆:272张图像
洋葱:357张图像
青椒:497张图像
大蒜:235张图像
萝卜:310张图像
豆类:454张图像
茄子:213张图像
黄瓜:232张图像
苦瓜:157张图像
苦瓜:93张图像
茄子(茄子):88张图像
番茄:37张图像
数据来源:图像采用移动电话相机拍摄,并去除背景以增强清晰度,聚焦于蔬菜本身。
应用范围:蔬菜分类模型、自动化农产品识别系统、计算机视觉基准测试、教育与农业研究。
提供机构:
Mendeley Data



