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.

印度是仅次于中国的全球第二大果蔬出口国，香蕉、木瓜和芒果的产量位居全球第一。目前公开的水果数据集多局限于通用水果类别，无法依据水果品质进行分类。构建本数据集的核心目标如下：1）聚焦印度出口量或消费量最高的六大类水果；2）构建支持按水果品质分类的数据集；3）本数据集涵盖12类水果，共计12000张高质量图像。我们采用手机后置摄像头采集水果图像，数据集总计12000张图像，涵盖12个类别，分别为坏苹果（Bad Apple）、好苹果（Good Apple）、坏香蕉（Bad Banana）、好香蕉（Good Banana）、坏番石榴（Bad Guava）、好番石榴（Good Guava）、坏青柠（Bad Lime）、好青柠（Good Lime）、坏橙子（Bad Orange）、好橙子（Good Orange）、坏石榴（Bad Pomegranate）、好石榴（Good Pomegranate）。数据集中每个类别包含1000张分辨率为256×256的图像，所有图像的拍摄角度、背景及光照条件均存在差异。由于本数据集选用的是国民消费量最高的水果品类，因此对相关研究人员具有较高的实用价值。

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12,000张高质量图像，涵盖苹果、香蕉、番石榴、酸橙、橙子和石榴六种水果的'好'与'坏'两种质量状态，每类1,000张图像。其设计目标是为计算机视觉和机器学习研究提供支持，特别适用于水果质量自动识别和分类任务，以弥补现有数据集仅按一般类别分类的不足。