Trash-ICRA19: A Bounding Box Labeled Dataset of Underwater Trash

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Trash-ICRA19: A Bounding Box Labeled Dataset of Underwater Trash

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Sattar, Junaed




This data was sourced from the J-EDI dataset of marine debris. The videos that comprise that dataset vary greatly in quality, depth, objects in scenes, and the cameras used. They contain images of many different types of marine debris, captured from real-world environments, providing a variety of objects in different states of decay, occlusion, and overgrowth. Additionally, the clarity of the water and quality of the light vary significantly from video to video. These videos were processed to extract 5,700 images, which comprise this dataset, all labeled with bounding boxes on instances of trash, biological objects such as plants and animals, and ROVs. The eventual goal is to develop efficient and accurate trash detection methods suitable for onboard robot deployment. It is our hope that the release of this dataset will facilitate further research on this challenging problem, bringing the marine robotics community closer to a solution for the urgent problem of autonomous trash detection and removal.


This dataset is available for download as a .zip file named Within the compressed folder are both the dataset and configurations for testing the datset with deep learning algorithms. There is a README in the top directory, and in most lower directories, explaining the files and directories in its directory.

Referenced by

M. Fulton, J. Hong, M. J. Islam and J. Sattar, "Robotic Detection of Marine Litter Using Deep Visual Detection Models," 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 5752-5758

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Fulton, Michael S; Hong, Jungseok; Sattar, Junaed. (2020). Trash-ICRA19: A Bounding Box Labeled Dataset of Underwater Trash. Retrieved from the Data Repository for the University of Minnesota (DRUM),
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File View/OpenDescriptionSize
trash_ICRA19.zipThis is a compressed folder containing the images, annotations, network weights, and configurations980.14 MB
README.txtDescription of the dataset at the top level844 B
LICENSE.txtLicense for the dataset. Free for academic/personal use, must contact JAMSTEC for license for commercial use.820 B

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