Dataset of 400 pomegranate tree (Punica granatum L. 'Wonderful') images

Dataset of 400 pomegranate tree (Punica granatum L. ‘Wonderful’) images, with the corresponding fruit masks. The dataset is designed for training artificial intelligence models for instance segmentation. The pictures were collected by means of mobile devices (smartphones), in random trees, from different distances, orientations and in varying lighting conditions. The resolution of the images and masks is 640x480 pixels. The dataset is divided into training (70%), validation (15%) and test set (15%). Stratification was performed in 3 periods of the season to ensure that all fruit ripening stages were present in each subset. Masks consist of a very detailed manual annotation of the visible part for each of the fruits in the images.本数据集包含400幅石榴树（Punica granatum L. ‘Wonderful’）图像，配套对应的果实掩码。本数据集专为训练实例分割类人工智能模型而构建。图像通过移动设备（智能手机）采集，拍摄对象为随机选取的石榴树，采集时涵盖了不同拍摄距离、拍摄角度与光照条件。图像与掩码的分辨率均为640×480像素。数据集按70%训练集、15%验证集与15%测试集的比例进行划分。为确保每个子集均覆盖所有果实成熟阶段，数据集依据季节的3个时段完成了分层抽样。所有掩码均为对图像中每颗果实可见部分的精细手工标注结果。

搜集汇总

背景与挑战

背景概述

这是一个包含400张石榴树（品种'Wonderful'）图像的数据集，每张图像都配有详细的果实掩码，专门用于训练人工智能模型进行实例分割。图像通过智能手机在不同距离、方向和光照条件下采集，分辨率为640x480像素，并已划分为训练、验证和测试集，确保覆盖所有果实成熟阶段，适用于精准农业和计算机视觉研究。