Pomegranate Images Dataset

The dataset consists of images capturing various growth stages of pomegranates. The images were collected from May to September in an orchard located within the Henan Institute of Science and Technology in China. There are a total of 5857 images in the dataset, and each image is labeled and classified into one of five periods: bud, flower, early-fruit, mid-growth, and ripe. The dataset was curated and hosted by the School of Computer Science and Technology at Henan University of Science and Technology, in collaboration with researchers from the Artificial Light Plant Factory at the same university. The purpose of creating this dataset is to support the development of computer applications that utilize machine learning and computer vision algorithms. By studying the different growth stages of pomegranates, researchers can effectively monitor the condition of each growth stage and enable early detection of any abnormal growth conditions. This early detection can be beneficial for farmers, as it can help them minimize economic losses.本数据集收录了记录石榴各生长阶段的图像。上述图像于5月至9月间，在中国河南科技学院内的一处果园采集完成。数据集总计包含5857张图像，每张图像均已完成标注与分类，共划分为5个生长阶段：萌芽期（bud）、花期（flower）、早果期（early-fruit）、生长中期（mid-growth）以及成熟期（ripe）。 本数据集由河南科技大学计算机科学与技术学院整理并托管，与该校人工光照植物工厂的研究人员合作完成。构建本数据集的初衷是为依托机器学习与计算机视觉算法的计算机应用开发提供支撑。通过对石榴不同生长阶段的研究，研究人员可实现对各生长阶段植株状态的有效监测，并提前识别生长异常状况。此类异常状况的早期识别可惠及种植户，帮助其最大限度降低经济损失。