Top Indian Fruits with quality

INDIA is the second-largest fruit and vegetable exporter in the world after China. It ranked first in the production of Bananas, Papayas, and Mangoes. Public datasets of fruits are available but they are limited to general fruit classes and failed to classify the fruits according to the fruit quality. The main objectives to create this dataset were: 1) Target the top six Indian fruits which are exported or highly consumed. 2) Create a dataset for fruit classification with the quality of fruit. 3) Dataset consists of 12000 high-quality images of 12 different classes of fruits.We use mobile phones rear camera to take the images of fruits. The dataset consists of total 12000 images with 12 classes namely, Bad Apple, Good Apple, Bad Banana, Good Banana, Bad Guava, Good Guava, Bad Lime, Good Lime, Bad Orange, Good Orange, Bad Pomegranate, and Good Pomegranate. In the dataset, each class consists of 1000 images of size 256x256. The images had taken with different angles, with different backgrounds, and in different lighting conditions. As we considered the most consumed fruits this dataset is very useful for researchers.

印度为全球仅次于中国的第二大果蔬出口国，其香蕉、木瓜与芒果的产量位居全球首位。当前公开的水果数据集多局限于通用水果类别，且无法依据水果品质进行分类。构建本数据集的三大目标如下：1）聚焦印度出口量较高或国内消费量居前的六大水果品类；2）创建可标注水果品质的水果分类数据集；3）该数据集包含12个类别共计12000张高质量图像。本数据集采用手机后置摄像头采集水果图像，总计包含12000张图像，涵盖12个类别，分别为：劣质苹果（Bad Apple）、优质苹果（Good Apple）、劣质香蕉（Bad Banana）、优质香蕉（Good Banana）、劣质番石榴（Bad Guava）、优质番石榴（Good Guava）、劣质青柠（Bad Lime）、优质青柠（Good Lime）、劣质橙（Bad Orange）、优质橙（Good Orange）、劣质石榴（Bad Pomegranate）、优质石榴（Good Pomegranate）。数据集中每个类别均包含1000张分辨率为256×256的图像，图像采集场景涵盖不同拍摄角度、背景环境与光照条件。鉴于本数据集选用的均为印度国内高消费量的水果，其对相关领域研究者具有极高的应用价值。

搜集汇总

背景与挑战

背景概述

该数据集名为FruitsGB，专注于印度主要水果的质量分类，包含12000张高质量图像，覆盖苹果、香蕉、番石榴、酸橙、橙子和石榴6种水果的12个类别（好与坏），每类1000张256x256像素图像，拍摄于不同角度、背景和光照条件。数据集旨在支持计算机视觉和机器学习研究，特别是水果分类与质量评估任务。