AmodalAppleSize_RGB-D
The AmodalAppleSize_RGB-D dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained from a Fuji and an Elstar apple orchards. The Fuji apple orchar...
| Autores: | , , , , , , , , , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Consorci de Serveis Universitaris de Catalunya (CSUC) |
| Repositorio: | CORA.Repositori de Dades de Recerca |
| OAI Identifier: | oai:dnet:cora.rdr____::80679afd72674239a457a3ec70b5e0ea |
| Acceso en línea: | https://doi.org/10.34810/DATA916 |
| Access Level: | acceso abierto |
| Palabra clave: | Agricultural Sciences Computer and Information Science yield forecasting fruit trees apples precision agriculture measurement Image segmentation Range imaging visibility robotics |
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AmodalAppleSize_RGB-DGené Mola, JordiFerrer Ferrer, MarHemming, JochenDalfsen, Pieter vanHoog, Dirk deSanz Cortiella, RicardoRosell Polo, Joan RamonMorros Rubió, Josep RamonVilaplana Besler, VerónicaRuiz Hidalgo, JavierGregorio López, EduardAgricultural SciencesComputer and Information Scienceyield forecastingfruit treesapplesprecision agriculturemeasurementImage segmentationRange imagingvisibilityroboticsThe AmodalAppleSize_RGB-D dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained from a Fuji and an Elstar apple orchards. The Fuji apple orchard sub-set consists of 3925 RGB-D images containing a total of 15335 apples annotated with both modal and amodal apple segmentation masks. Modal masks denote the visible portions of the apples, whereas amodal masks encompass both visible and occluded apple regions. Notably, this dataset is the first public resource to incorporate fruit amodal masks. This pioneering inclusion addresses a critical gap in existing datasets, enabling the development of robust automatic fruit sizing methods and accurate fruit visibility estimation, particularly in the presence of partial occlusions. Besides the fruit segmentation masks, the dataset also includes the fruit size (calliper) ground truth for each annotated apple. The second sub-set comprises 2731 RGB-D images capturing five Elstar apple trees at four distinct growth stages. This sub-set includes mean diameter information for each tree at every growth stage and serves as a valuable resource for evaluating fruit sizing methods trained with the first sub-set. The present data was employed in the research paper titled "Looking behind occlusions: a study on amodal segmentation for robust on-tree apple fruit size estimation".CORA.Repositori de Dades de RecercaUniversitat de Lleida (UdL) - Agrotecnio-CERCA center, Grup de Recerca AgròTICa i Agricutura de Precisió2023info:eu-repo/semantics/datasethttps://doi.org/10.34810/DATA916reponame:CORA.Repositori de Dades de Recercainstname:Consorci de Serveis Universitaris de Catalunya (CSUC)InglésGené Mola, Jordi; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Escolà i Agustí, Alexandre; Gregorio López, Eduard. (2021). PFuji-Size dataset: photogrammetry-derived 3D point clouds of Fuji apples trees with annotations to evaluate fruit detection and size estimation methodologies. CORA.Repositori de Dades de Recerca. https://doi.org/10.34810/data141Jordi Gene-Mola, Ricardo Sanz-Cortiella, Joan R. Rosell-Polo, Josep-Ramon Morros, Javier Ruiz-Hidalgo, Verónica Vilaplana, & Eduard Gregorio. (2020). Fuji-SfM dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3712808Gené Mola, Jordi; Gregorio López, Eduard; Auat Cheein, Fernando; Guevara, Javier; Llorens Calveras, Jordi; Sanz Cortiella, Ricardo; Escolà i Agustí, Alexandre; Rosell Polo, Joan Ramon. (2020). LFuji-air dataset. Repositori Obert UdL. http://hdl.handle.net/10459.1/68782Jordi Gené-Mola, Verónica Vilaplana, Joan R. Rosell-Polo, Josep-Ramon Morros, Javier Ruiz-Hidalgo, & Eduard Gregorio. (2020). KFuji RGB-DS dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3715991info:eu-repo/semantics/openAccessCC BY 4.0oai:dnet:cora.rdr____::80679afd72674239a457a3ec70b5e0ea2026-06-17T12:20:17Z |
| dc.title.none.fl_str_mv |
AmodalAppleSize_RGB-D |
| title |
AmodalAppleSize_RGB-D |
| spellingShingle |
AmodalAppleSize_RGB-D Gené Mola, Jordi Agricultural Sciences Computer and Information Science yield forecasting fruit trees apples precision agriculture measurement Image segmentation Range imaging visibility robotics |
| title_short |
AmodalAppleSize_RGB-D |
| title_full |
AmodalAppleSize_RGB-D |
| title_fullStr |
AmodalAppleSize_RGB-D |
| title_full_unstemmed |
AmodalAppleSize_RGB-D |
| title_sort |
AmodalAppleSize_RGB-D |
| dc.creator.none.fl_str_mv |
Gené Mola, Jordi Ferrer Ferrer, Mar Hemming, Jochen Dalfsen, Pieter van Hoog, Dirk de Sanz Cortiella, Ricardo Rosell Polo, Joan Ramon Morros Rubió, Josep Ramon Vilaplana Besler, Verónica Ruiz Hidalgo, Javier Gregorio López, Eduard |
| author |
Gené Mola, Jordi |
| author_facet |
Gené Mola, Jordi Ferrer Ferrer, Mar Hemming, Jochen Dalfsen, Pieter van Hoog, Dirk de Sanz Cortiella, Ricardo Rosell Polo, Joan Ramon Morros Rubió, Josep Ramon Vilaplana Besler, Verónica Ruiz Hidalgo, Javier Gregorio López, Eduard |
| author_role |
author |
| author2 |
Ferrer Ferrer, Mar Hemming, Jochen Dalfsen, Pieter van Hoog, Dirk de Sanz Cortiella, Ricardo Rosell Polo, Joan Ramon Morros Rubió, Josep Ramon Vilaplana Besler, Verónica Ruiz Hidalgo, Javier Gregorio López, Eduard |
| author2_role |
author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
Universitat de Lleida (UdL) - Agrotecnio-CERCA center, Grup de Recerca AgròTICa i Agricutura de Precisió |
| dc.subject.none.fl_str_mv |
Agricultural Sciences Computer and Information Science yield forecasting fruit trees apples precision agriculture measurement Image segmentation Range imaging visibility robotics |
| topic |
Agricultural Sciences Computer and Information Science yield forecasting fruit trees apples precision agriculture measurement Image segmentation Range imaging visibility robotics |
| description |
The AmodalAppleSize_RGB-D dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained from a Fuji and an Elstar apple orchards. The Fuji apple orchard sub-set consists of 3925 RGB-D images containing a total of 15335 apples annotated with both modal and amodal apple segmentation masks. Modal masks denote the visible portions of the apples, whereas amodal masks encompass both visible and occluded apple regions. Notably, this dataset is the first public resource to incorporate fruit amodal masks. This pioneering inclusion addresses a critical gap in existing datasets, enabling the development of robust automatic fruit sizing methods and accurate fruit visibility estimation, particularly in the presence of partial occlusions. Besides the fruit segmentation masks, the dataset also includes the fruit size (calliper) ground truth for each annotated apple. The second sub-set comprises 2731 RGB-D images capturing five Elstar apple trees at four distinct growth stages. This sub-set includes mean diameter information for each tree at every growth stage and serves as a valuable resource for evaluating fruit sizing methods trained with the first sub-set. The present data was employed in the research paper titled "Looking behind occlusions: a study on amodal segmentation for robust on-tree apple fruit size estimation". |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/dataset |
| format |
dataset |
| dc.identifier.none.fl_str_mv |
https://doi.org/10.34810/DATA916 |
| url |
https://doi.org/10.34810/DATA916 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
Gené Mola, Jordi; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Escolà i Agustí, Alexandre; Gregorio López, Eduard. (2021). PFuji-Size dataset: photogrammetry-derived 3D point clouds of Fuji apples trees with annotations to evaluate fruit detection and size estimation methodologies. CORA.Repositori de Dades de Recerca. https://doi.org/10.34810/data141 Jordi Gene-Mola, Ricardo Sanz-Cortiella, Joan R. Rosell-Polo, Josep-Ramon Morros, Javier Ruiz-Hidalgo, Verónica Vilaplana, & Eduard Gregorio. (2020). Fuji-SfM dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3712808 Gené Mola, Jordi; Gregorio López, Eduard; Auat Cheein, Fernando; Guevara, Javier; Llorens Calveras, Jordi; Sanz Cortiella, Ricardo; Escolà i Agustí, Alexandre; Rosell Polo, Joan Ramon. (2020). LFuji-air dataset. Repositori Obert UdL. http://hdl.handle.net/10459.1/68782 Jordi Gené-Mola, Verónica Vilaplana, Joan R. Rosell-Polo, Josep-Ramon Morros, Javier Ruiz-Hidalgo, & Eduard Gregorio. (2020). KFuji RGB-DS dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3715991 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess CC BY 4.0 |
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openAccess |
| rights_invalid_str_mv |
CC BY 4.0 |
| dc.publisher.none.fl_str_mv |
CORA.Repositori de Dades de Recerca |
| publisher.none.fl_str_mv |
CORA.Repositori de Dades de Recerca |
| dc.source.none.fl_str_mv |
reponame:CORA.Repositori de Dades de Recerca instname:Consorci de Serveis Universitaris de Catalunya (CSUC) |
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Consorci de Serveis Universitaris de Catalunya (CSUC) |
| reponame_str |
CORA.Repositori de Dades de Recerca |
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CORA.Repositori de Dades de Recerca |
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15,811543 |