This chipped training dataset is over Dar es Salaam and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 566 tiles and 8,485 buildings. The original dataset was sourced from the Open Cities AI Challenge Dataset before the drone imagery was resampled to 30 cm and the labeled data were improved. Dataset keywords: Urban, Dense.
DevGlobal, (2022). ramp Building Footprint Training Dataset - Dar es Salaam, Tanzania, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.895jh7
from radiant_mlhub import Dataset ds = Dataset.fetch('ramp_daressalaam_tanzania') for c in ds.collections: print(c.id)
ramp Building Footprint Training Dataset - Dar es Salaam, Tanzania - Source Imagery
ramp Building Footprint Training Dataset - Dar es Salaam, Tanzania - Labels