Candy Dataset - Faculty of Engineering - University of Porto - Department of Mechanical Engineering

Published: 15 January 2025| Version 1 | DOI: 10.17632/n3gcx2ds6t.1
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Description

This repository presents the "Candy Dataset". The repository contains a single file that comprises an authentic dataset. For user convenience, it is available for download in various formats, including YOLOV11, YOLOV10, YOLOV9, YOLOv8, YOLOV6,YOLOv5, YOLOv7, MT-YOLOv6, COCO JSON, YOLO Darknet, Pascal VOC XML, TFRecord, CreateML JSON, and Other Formats. Ultimately, this dataset is available for download in zip format. Also includes the kinematic and dynamic parameters of the Collaborative Robot. Any publications utilizing the 'Candy Dataset' must properly cite the following paper: Santos, A.A., Schreurs, C., da Silva, A.F. et al. Integration of Artificial Vision and Image Processing into a Pick and Place Collaborative Robotic System. J Intell Robot Syst 110, 159 (2024). https://doi.org/10.1007/s10846-024-02195-z

Files

Steps to reproduce

This repository presents the "Candy Dataset". The repository contains a single file that comprises an authentic dataset. For user convenience, it is available for download in various formats, including YOLOV11, YOLOV10, YOLOV9, YOLOv8, YOLOV6,YOLOv5, YOLOv7, MT-YOLOv6, COCO JSON, YOLO Darknet, Pascal VOC XML, TFRecord, CreateML JSON, and Other Formats. Ultimately, this dataset is available for download in zip format. Also includes the kinematic and dynamic parameters of the Collaborative Robot. Any publications utilizing the 'Candy Dataset' must properly cite the following paper: Santos, A.A., Schreurs, C., da Silva, A.F. et al. Integration of Artificial Vision and Image Processing into a Pick and Place Collaborative Robotic System. J Intell Robot Syst 110, 159 (2024). https://doi.org/10.1007/s10846-024-02195-z

Institutions

Instituto Politecnico do Porto Instituto Superior de Engenharia do Porto, Universidade do Minho Departamento de Engenharia Mecanica, Institutul National de Cercetare-Dezvoltare pentru Mecatronica si Tehnica Masurarii, Universidade do Porto Departamento de Engenharia Mecanica, Universitatea Titu Maiorescu, Universidade do Porto Faculdade de Engenharia, Universitatea Politehnica din Bucuresti

Categories

Artificial Intelligence, Robotics, Kinematics, Robot, Experimental Robotics, Deep Learning, Database, Manufacturing Robotics, YOLOv5, YOLOv7

Funding

European Commission

European Union – NextGenerationEU and Romanian Government, under National Recovery and Resilience Plan for Romania: contract no. 760071/23.05.2023, code CF 121/15.11.2022

Related Links

Article
https://link.springer.com/article/10.1007/s10846-024-02195-z
cites this dataset

Licence