Dataset of Banana Prata Catarina Images Labeled in Eight Ripeness Stages

Published: 30 May 2023| Version 1 | DOI: 10.17632/7vb4djkbrc.1
José Luciano, João Pedro Holanda Neves, Marcus Vinicius, Emannuel Diego Gonçalves de Freitas, Danielo G. Gomes


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.


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After capture, they were uploaded to the project created on the Roboflow website, where they were separated by the abbreviations of the marker's name with the date of the upload day next to it and received the appropriate classification using the bounding boxes method. The photographs were taken in similar situations, photographed without flash and saved in '.jpg' format.


Instituto Federal de Educacao Ciencia e Tecnologia do Ceara, Universidade Federal do Ceara


Computer Vision, Machine Learning, Banana