Radiant MLHub

ramp Building Footprint Training Dataset - Accra, Ghana

This chipped training dataset is over Accra 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 1,330 tiles and 40,786 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.

Dataset ID

ramp_accra_ghana

DOI

10.34911/rdnt.zyiv7t

Creator

DevGlobal

Contact

info@dev.global

Documentation

Tools & Applications

Citation

DevGlobal, (2022). ramp Building Footprint Training Dataset - Accra, Ghana, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.zyiv7t

Python Client example

from radiant_mlhub import Dataset

ds = Dataset.fetch('ramp_accra_ghana')
for c in ds.collections:
    print(c.id)

Python Client quick-start guide

Download Dataset

Source Imagery Collections

Description

ramp Building Footprint Training Dataset - Accra, Ghana - Source Imagery

License

CC-BY-SA-4.0

Collection ID

ramp_accra_ghana_source

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Labels Collections

Description

ramp Building Footprint Training Dataset - Accra, Ghana - Labels

License

CC-BY-SA-4.0

Collection ID

ramp_accra_ghana_labels

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