Dataset of Banana Prata Catarina Images Labeled in Eight Ripeness Stages

Our general objective is that the dataset proposed here be useful for the development of Machine Learning and Computer Vision algorithms whose central object of analysis is the banana. The images contained here are of bananas from the Prata Catarina cultivar, with labeling of eight classes that represent levels of control of the fruit. For the labeling process, they were labeled via Bounding box, demarcating the banana in the image and assigning it a degree of maturation following the norms proposed in CEAGESP (2006). All 1000 images of bananas were taken using only smartphones. These images were collected on February 4th, 13th and 17th, 2023, with variations of the background on a smooth surface (white marble), on clayey soil or on foliage. Lastly, all data was uploaded to the roboflow platform and labeled using the bounding boxes method.本数据集的核心研发目标，是为以香蕉为核心分析对象的机器学习与计算机视觉算法开发提供支撑。本数据集包含的图像均取自普拉塔卡塔琳娜（Prata Catarina）品种的香蕉，共标注有八个类别，分别对应香蕉的成熟度管控等级。标注环节采用边界框（Bounding box）对图像中的香蕉进行框选，并依据CEAGESP（2006）提出的规范为其赋予对应成熟度等级。本次采集的全部1000张香蕉图像，均仅使用智能手机拍摄完成。这批图像采集于2023年2月4日、13日及17日，拍摄背景存在多样变化，涵盖光滑平面（白色大理石台面）、黏质土壤以及植物叶面三种场景。最后，所有数据均上传至Roboflow平台，并通过边界框标注法完成全部标注工作。