DeepSpaceYoloDataset
Introduced by Parisot et al. in Détection d'objets célestes dans des images astronomiques par IA explicable
During the MILAN research project (MachIne Learning for AstroNomy), we have compiled a large collection of deep sky images during Electronically Assisted Astronomy sessions in Luxembourg, France, Belgium.
We have used two instruments for several months (from March 2022 to September 2023): a Stellina smart telescope (https://vaonis.com/stellina) and a Vespera smart telescope (https://vaonis.com/vespera). We have captured data for a representative set of deep sky objects from the Messier / NGC / IC / Sharpless2 / Barnard catalogues. Different types of celestial objects were considered: emission/reflection/dark/planetary nebula, galaxies, globular/open clusters. Images were obtained after the capture and the stacking of sub-frames of 10 seconds exposure time. Training images were splitted into 608x608 patches. Based on the YOLOv7 format, the dataset is a ZIP file containing 4696 RGB images, and the corresponding 4696 labels text files with the positions of deep sky objets in the images.
This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.
More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.
More information about VAONIS instruments: https://vaonis.com
More information about Luxembourg of Science and Technology (LIST): https://www.list.lu
Papers
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