CERTH Grape Dataset

The CERTH grape dataset aims to advance computer vision and machine learning research in the field of viticulture by providing valuable annotated data for developing and refining algorithms for accurate grape segmentation, yield prediction, and, most importantly, maturity estimation. The dataset consists of 2502 high-resolution images captured from a vineyard cultivating the 'Crimson Seedless' table grape variety during the 2022–2023 development and harvesting period and exhibits different view angles, camera focus conditions, and illumination variations. The images are captured using an iPhone 11 Pro smartphone and are scaled to a resolution of 2160 × 3840 pixels. The annotations include grape bunches with detailed object masks and are categorized into three distinct classes (i.e., immature, semi-mature, and mature) based on the degree of grape maturity, as identified by the color of the grapes in the bunch. As a result, grapes in the immature class were early in their development phase, grapes in the mature class were close to the harvesting season, and grapes in the semi-mature class were in the intermediate period when changes in the color of the grapes from yellow to red had initiated. The CERTH grape dataset consists of 9832 labeled grape bunches, extracted from all 2502 images. The grape images are split into training, validation, and test sets, consisting of 2000, 251, and 251 images, respectively. The training set comprises 7959 annotated grape bunches, while the validation and test sets comprise 914 and 959 annotated grape bunches, respectively. The CERTH grape datasets can be evaluated on two scenarios. The multi-instance / multi-class (mimc) scenario evaluates the performance of algorithms in multi-instance classification using the original test set, while the single-instance / one-class (sioc) scenario extracts 100 images from the original test set that contain a single grape bunch per image to evaluate the performance of algorithms in single-instance classification. The sioc subset consists of 36, 43, and 21 images that depict grape bunches from the immature, semi-mature, and mature classes, respectively. To use this dataset, please also cite: Blekos, A.; Chatzis, K.; Kotaidou, M.; Chatzis, T.; Solachidis, V.; Konstantinidis, D.; Dimitropoulos, K. A Grape Dataset for Instance Segmentation and Maturity Estimation. Agronomy 2023, 13, 1995. https://doi.org/10.3390/agronomy13081995.