Synthetic Training Dataset for Real-World Terminal Strip Object Detection Baumgart, Nico Lange-Hegermann, Markus Mücke, Mike Object Detection Image Synthesis Domain Randomization Domain Gap Terminal Strip This dataset provides synthetic training data for the real-world industrial application of terminal strip object detection to investigate the sim-to-real generalization performance of modern object detectors based on state-of-the-art image synthesis methods. It consists of 30.000 randomly generated synthetic images of terminal strips covering 36 different terminal blocks in five colors and additional accessories such as plug-in bridges, test adapters, end covers and markings. Except from the markings and the DIN rail all objects of the terminal strips are labeled with a bounding box and the respective object class for supervised learning. Additionally, 300 real images of terminal strips were taken and manually labeled for the real-world test. If you use this datset for your research, please consider citing this: Investigation of the Impact of Synthetic Training Data in the Industrial Application of Terminal Strip Object Detection Zenodo 2024 info:eu-repo/semantics/other doc-type:ResearchData text http://purl.org/coar/resource_type/c_ddb1 https://www.th-owl.de/elsa/record/13824 Baumgart N, Lange-Hegermann M, Mücke M. <i>Synthetic Training Dataset for Real-World Terminal Strip Object Detection</i>. Zenodo; 2024. doi:<a href="https://doi.org/10.5281/ZENODO.16080102">10.5281/ZENODO.16080102</a> info:eu-repo/semantics/altIdentifier/doi/10.5281/ZENODO.16080102 info:eu-repo/semantics/closedAccess