FOSSBot Object Detection dataset

Published: 3 July 2026| Version 2 | DOI: 10.17632/ft68smsyhf.2
Contributor:
Marcin Czajka

Description

This dataset consists of synthetic images created for object detection tasks, featuring five target classes: a cactus, a traffic cone, a fire hydrant, a pallet, and a traffic light. The images were generated using NVIDIA Isaac Sim, where the target objects were spawned alongside various assets from NVIDIA Omniverse acting as environmental obstacles. The dataset includes automatically generated bounding box annotations in YOLO format, making it ready for immediate use in training object detection models. It was created specifically for the FOSSBot4AI course: https://put-jug.github.io/lab-intro-to-robotics/. EU funding disclaimer Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.

Files

Steps to reproduce

To recreate the dataset please refer to the `dataset_collection` directory in our repository: https://github.com/LRMPUT/fossbot-object-detection

Categories

Computer Vision, Robotics, Object Detection, Mobile Robot

Funders

  • European Union

Licence