ESSA PyTorch Model Checkpoint and Shapefiles Containing Pit and Skylight Detections on the Moon

This dataset contains the PyTorch model checkpoint file (also called the state_dict) of ESSA - a Mask R-CNN instance segmentation Deep Learning model trained to detect pits and skylights within Lunar Reconnaissance Orbiter Narrow Angle Camera (LROC NAC) imagery of the Moon. Instructions on how to load a model checkpoint in order to re-train or infer it on your own data can be found here.

The .zip file ESSA_shapefiles.zip contains the locations of the pit and skylight detections made by ESSA within eight Regions of Interest for searching for potential cave entrances ('ESSA_detections.shp'). These detections are in ESRI shapefile format ready for viewing in GIS software such as QGIS or ArcGIS. We also provide shapefiles of the mapping of Lunar rilles within the Marius Hills region of the Moon ('marius_hills_rilles.shp'). Both of these sets of shapefiles have attribute fields containing the confidence scores that they were detected with and the images that they were found to be within.